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How do CD 8+ Tc cells reach the site of tumors?

How do CD 8+ Tc cells reach the site of tumors?



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In normal humoral immunity, dendritic cells present antigens to the Th cells by arriving at the Lymph node. This is fine. But consider a tumor cell. How does the Tc cell sitting in the lymph node know that there is problem out there? Consider there is a single cell which has undergone mutations and is expressing altered proteins. This wouldn't cause much inflammation to attract the Tc cell there.

So, is there continuous surveillance by the Tc cells? Where exactly do the Tc cells reside? Do they roam around like Th cells? How about the NK cells? do they too roam around in the tissues?

Cases of viral and intracellular pathogens, there may be some inflammation which draws the Tc cells there. Maybe. This can not be in tumors. So how do the Tc cells reach there?


I do not remember enough details to share a mechanistic insight.

However, chemotaxis is a likely answer, which basically means moving along concentration gradient of certain ligand of interest.

Also relevant to your question: a hypothesis called 'immune surveillance' gaining support over the past few years.

http://www.biolegend.com/cancerimmunoediting


T-Cell and NK-Cell Infiltration into Solid Tumors: A Key Limiting Factor for Efficacious Cancer Immunotherapy

Summary: Cancer immunotherapy has great promise, but is limited by diverse mechanisms used by tumors to prevent sustained antitumor immune responses. Tumors disrupt antigen presentation, T/NK–cell activation, and T/NK–cell homing through soluble and cell-surface mediators, the vasculature, and immunosuppressive cells such as myeloid-derived suppressor cells and regulatory T cells. However, many molecular mechanisms preventing the efficacy of antitumor immunity have been identified and can be disrupted by combination immunotherapy. Here, we examine immunosuppressive mechanisms exploited by tumors and provide insights into the therapies under development to overcome them, focusing on lymphocyte traffic. Cancer Discov 4(5) 522–6. ©2014 AACR.


Abstract

The tumor microenvironment plays a critical role in controlling tumor progression and immune surveillance. We produced an immunotoxin (2E4-PE38) that kills mouse cells expressing CD25 by attaching the Fv portion of monoclonal antibody 2E4 (anti-mouse CD25) to a 38-kDa portion of Pseudomonas exotoxin A. We employed three mouse cancer tumor models (AB1 mesothelioma, 66c14 breast cancer, and CT26M colon cancer). Tumors were implanted at two sites on BALB/c mice. On days 5 and 9, one tumor was directly injected with 2E4-PE38, and the other was not treated 2E4-PE38 produced complete regressions of 85% of injected AB1 tumors, 100% of 66c14 tumors, and 100% of CT26M tumors. It also produced complete regressions of 77% of uninjected AB1 tumors, 47% of 66c14 tumors, and 92% of CT26M tumors. Mice with complete regressions of 66c14 tumors were immune to rechallenge with 66c14 cells. Mice with complete regressions of AB1 or CT26M tumors developed cross-tumor immunity rejecting both tumor types. Injection of anti-CD25 antibody or a mutant inactive immunotoxin were generally ineffective. Tumors were analyzed 3 days after 2E4-PE38 injection. The number of regulatory T cells (Tregs) was significantly reduced in the injected tumor but not in the spleen. Injected tumors contained an increase in CD8 T cells expressing IFN-γ, the activation markers CD69 and CD25, and macrophages and conventional dendritic cells. Treatment with antibodies to CD8 abolished the antitumor effect. Selective depletion of Tregs in tumors facilitates the development of a CD8 T cell-dependent antitumor effect in three mouse models.

The concept of suppressor T cells was proposed in the 1970s (1). However, the existence of suppressor T cells as a distinct lineage of T cells was controversial (2). In the mid-1990s, the concept of regulatory T cells (Tregs) was proposed, and since then Tregs have been extensively studied in mice and in humans (3). It is now well established that Tregs are a distinct lymphocyte lineage endowed with regulatory properties that affect a variety of immune cells (4). Tregs play an important role in immune escape by suppressing antitumor immunity, thereby providing an environment of immune tolerance. T cells that recognize cancer cells are often present in large numbers in tumors, but their cytotoxic function is suppressed by nearby immune-suppressor cells. Tregs are abundant in many different cancers (5), are highly enriched in the tumor microenvironment, and are well known for their role in tumor progression.

It has been demonstrated that Tregs contribute to the early establishment and progression of tumors in murine models and that their absence results in delay of tumor progression (6 ⇓ ⇓ –9). High tumor infiltration by Tregs and a low ratio of effector T cells (Teffs) to Tregs is associated with poor outcome in solid tumors (10). Conversely, a high Teff/Treg cell ratio is associated with responses to immunotherapy (11). To date, most studies support the notion that targeting Tregs, either by depletion or functional modulation, offers a significant therapeutic benefit, particularly in combination with other immune modulatory interventions such as vaccines and checkpoint blockade (12 ⇓ ⇓ –15). Defining appropriate targets for selective interference with Tregs is a critical step in the development of effective therapies. In this regard, CD25, also known as the interleukin-2 high-affinity receptor alpha chain (IL-2Rα), was the first surface marker used to identify Tregs (3) before the discovery of their master regulator, transcription factor fork-head box p3 (Foxp3). CD25 is also the most extensively studied target for inhibiting or eliminating Tregs and is absent on naive Teffs. However, transient up-regulation of CD25 has been observed upon activation of Teffs (16).

A number of preclinical studies in mice have used an anti-CD25 antibody, which partially depletes Tregs in the blood and peripheral lymphoid organs (9, 17). When the antibody was administered before tumor challenge, there was inhibition of tumor growth and improved survival (7 ⇓ –9, 14, 18, 19). However, the administration of anti-CD25 antibody against established tumors has failed to delay tumor growth (7 ⇓ –9, 19). This has been attributed to several factors, including poor T cell infiltration of the tumor (14) and potential depletion of activated effector CD8+ and CD4+ T cells that up-regulate CD25 (9). Clinical studies exploring the use of vaccines in combination with daclizumab, a humanized IgG1 anti-human CD25 antibody, or denileukin diftitox, a recombinant fusion protein combining human IL-2 and a fragment of diphtheria toxin, or LMB-2, a recombinant fusion protein combining anti-human CD25 Fv and a fragment of Pseudomonas exotoxin A (PE) had a variable impact on the number of circulating Tregs and vaccine-induced immunity (20 ⇓ ⇓ ⇓ –24). Assessment of Foxp3 transcript levels in the tumors provides no clear evidence that Tregs in the tumor microenvironment were effectively reduced, and antitumor activity has been disappointing across all studies, with no survival benefit (20 ⇓ ⇓ ⇓ –24).

It is widely recognized that immune modulatory antibody-based therapies can affect the level of Tregs and that the antibody isotype is important (25 ⇓ ⇓ ⇓ –29). We have now re-evaluated CD25 as a target for Treg depletion in vivo, but instead of using a monoclonal antibody (mAb), we have used a locally injected recombinant immunotoxin (RIT) with potent cytotoxic activity for killing Tregs. Systemic blockade of Tregs has produced life-threatening and dose-limiting autoimmune side effects in patients because the expression of CD25 is not limited to Tregs Teffs also express CD25 (30). To maintain self-tolerance and proper control of adaptive immune responses, there must be a balance between Tregs and Teffs. Consequently, systemic depletion of Tregs may not be a good choice for cancer treatment, and we have used local therapy to avoid systemic side effects.

We have previously published that injection of an immunotoxin that targets mesothelin directly into tumors induces antitumor immunity when combined with anti–CTLA-4 (31). We have also reported that systemic injection of an immunotoxin targeting CD25 intravenously causes transient depletion of Tregs in the circulation, but no antitumor activity was observed (23). In the current study, we have taken advantage of our observation that intratumor injection of an immunotoxin can help initiate systemic immunity, and that injected immunotoxin (2E4-PE38) selectively kills T cells in the tumor, but does not deplete T cells outside the tumor. Using only the anti-CD25 immunotoxin, we have treated three different types of mouse cancers: 66c14 breast cancer, AB1 mesothelioma, and CT26M colon cancer. We have found that the immunotoxin caused complete regressions of the injected tumors, as well as most distal uninjected tumors and induced systemic antitumor immunity.


Amino Acids (PET and Single-Photon Emission Computed Tomography)

Besides FDG, radiolabeled amino acids are the most commonly used PET tracers for brain tumors. An advantage of using radiolabeled amino acids over FDG is the relatively low uptake of amino acids by normal brain tissue. Therefore, cerebral gliomas can be distinguished from the surrounding normal tissue with higher contrast compared with FDG. Many natural amino acids and their synthetic analogs have been labeled and explored as tumor imaging agents. 39 Most PET studies of cerebral gliomas have been performed with the amino acid [ 11 C]methyl- l -methionine ( 11 C-MET), 40 although the short half-life of 11 C (20 minutes) limits the use of this tracer to the few PET centers that are equipped with an in-house cyclotron facility. The increasing use of 18 F-labeled amino acids (half-life: 109 minutes), such as O-(2- 18 F-fluoroethyl)- l -tyrosine ( 18 F-FET) will probably replace 11 C-MET in the future. 41 Furthermore, single-photon emission computed tomography (SPECT) has been applied using radioiodinated amino acids such as l -3[ 123 I]iodo-α-methyl tyrosine (IMT) or p-[ 123 I]iodo- l -phenylalanine. 42,43 The results obtained with SPECT using amino acid tracers are, in general, similar to those with PET, but the poorer spatial resolution of SPECT represents a major disadvantage in clinical practice.

As it is beyond the scope of this review to consider all radiolabeled amino acids applied in brain tumors, this chapter is focused on the clinical experiences with 11 C-MET, 18 F-FET, and 123 I-IMT, which are at present the best validated amino acid tracers for PET and SPECT.

The increased uptake of 11 C-MET, 18 F-FET, and 123 I-IMT by cerebral glioma tissue appears to be caused almost entirely by increased transport via specific amino acid transporters, namely amino acid transport system L for large neutral amino acids. 44,45 11 C-MET also shows some incorporation into protein and participation in other metabolic pathways 40 however, comparative studies between 11 C-MET, 18 F-FET, and 123 I-IMT have shown that imaging of cerebral gliomas is similar with these amino acids. 46-48 Therefore, the participation of 11 C-MET in other metabolic pathways than transport appears to be of minor importance, and the clinical results obtained with the different tracers can be considered together. Because large neutral amino acids also enter normal brain tissue, a disruption of the BBB, that is, enhancement of contrast media in CT or MRI scans, is not a prerequisite for intratumoral accumulation of these amino acids. Consequently, uptake of the tracers has been reported in many LGG without BBB leakage. 49-51 The sensitivity and specificity of PET using 11 C-MET and 18 F-FET and SPECT using 123 I-IMT to differentiate between gliomas and non-neoplastic lesion is in the range of 70%-90%, 50,52,53 and the possibility of non-specific enhancement in inflammatory cells or reactive glial tissue must be borne in mind. There have been reports of perifocal 11 C-MET and 18 F-FET uptake around hematomas and areas of ischemia, as well as of rare cases of uptake in or around ring-enhancing lesions like brain abscesses and acute inflammatory demyelination. 40,54 Therefore, the predictive value is limited, and a histologic evaluation by biopsy remains the gold standard in the majority of unknown space-occupying lesions in the brain.

Imaging of Tumor Extent Biopsy and Treatment Planning

One of the most important aspects in the initial diagnosis of gliomas is the identification of tumor extension and the metabolically most active areas of the tumor. Representative tissue samples are important for histologic tumor diagnosis, prognostication, and treatment planning. The ability of MRI to show the most rapidly proliferating portions of the usually inhomogeneous gliomas is limited, particularly when the tumor does not take up contrast medium at CT or MRI. Multiple studies in which the radiological findings were compared with the histologic findings in tissue samples obtained by biopsy or open surgery have provided evidence that radiolabeled amino acids detect the solid mass of gliomas and metabolically active tumor areas more reliably than either CT or MRI. 55-59 This helps to prevent the problem of nondiagnostic biopsies from nonspecifically altered tissue and to plan surgical resection ( Fig. 3 ). A recent study demonstrated that integrating 11 C-MET-PET into the image-guided resection of HGG provided a final target contour different from that obtained with MRI alone in approximately 80% of the procedures. 60 Complete resection of the tumor area with increased amino acid uptake resulted in significantly longer survival of patients, whereas MRI enhancement on the postoperative scan did not have an impact on survival. Similarly, the amount of residual tracer uptake in 123 I-IMT-SPECT and 18 F-FET-PET had a strong prognostic influence. 61,62 These data indicate that resection of malignant gliomas guided by amino acid PET may increase the amount of anaplastic tissue removed and thus the patient’s survival. The improved imaging of glioma tissue using amino acid PET has also attracted interest for RT treatment planning. 63,64 A number of centers have started to integrate amino acid imaging into CT- and MRI-based radiotherapy planning, particularly when high-precision radiotherapy is to be given, in the setting of dose escalation studies, or for the reirradiation of recurrent tumors. 65-69 However, improved outcome of the patients with radiotherapy planning by amino acid imaging compared with conventional therapy planning has not yet been proven.

Oligoastrocytoma, WHO grade II: T1-weighted MRI after application of Gd-DTPA (A) shows no contrast enhancement. T2-weighted MRI scan (B) shows widespread abnormalities. (C) O-(2- 18 F-fluoroethyl)- l -tyrosine ( 18 FFET-PET) identifies metabolically active areas within the tumor and indicates an optimal site for biopsy.

Grading of Gliomas and Prognosis

Most studies using amino acid imaging have shown that gliomas of different WHO grades overlap in their degree of amino acid uptake therefore, the tumor grade cannot be reliably predicted with this technique. 40,51,58,70 However, a more reliable grading appears to be possible with 18 F-FET-PET, as this tracer exhibits differences in the time activity curves of tracer uptake depending on tumor grade. 71 HGG are characterized by an early peak approximately 10-15 minutes after injection followed by a decrease of 18 F-FET uptake, whereas LGG typically exhibit delayed and steadily increasing tracer uptake. Using dynamic 18 F-FET-PET, a differentiation of HGG and LGG has been reported in primary tumors and in recurrent tumors with an accuracy of 㺐%. 72-75

The prognostic significance of increased amino acid uptake in gliomas is controversial. Some studies seem to show that lower amino acid uptake especially in astrocytic glioma is associated with a better prognosis, but there may be a high uptake in oligodendrogliomas, despite their apparently better prognosis. 40,75,76 However, there appears to be a consensus concerning the clinical role of amino acid imaging in prognostication for patients with LGG. Significant longer survival has been reported for patients with lower 11 C-MET uptake in the tumors compared with those with higher uptake (cutoff of the tumor to brain ratio: 2.1). 77,78 Furthermore, the patients had a benefit from a surgical procedure only when increased 11 C-MET uptake was present. 77 Using 18 F-FET-PET, the combination with MR morphology has also been found to be a significant prognostic predictor for patients with newly diagnosed LGG. 49 Baseline 18 F-FET uptake and a circumscribed versus a diffuse growth pattern on MRI were highly significant predictors for patients’ course and outcome.

Assessment of Recurrent Tumors

A number of studies have shown that using 18 F-FET-PET and 123 I-IMT-SPECT, recurrent tumors can be differentiated from non-neoplastic posttherapeutic changes, with a sensitivity and specificity of approximately 90% ( Fig. 4 and ​ and5 5 ). 21,22,79-81 The sensitivity of 11 C-MET-PET for tumor recurrence is similar, whereas the specificity appears to be lower and has been reported to be in the range of 60%-80%. 17,20,40 This observation may be explained by a higher affinity of 11 C-MET for macrophages compared with 18 F-FET as demonstrated in animal experiments. 82,83 Additional use of dynamic 18 F-FET-PET allowed a differentiation of recurrences of HGG and LGG with a sensitivity and specificity of 92%. 74

Inhomogeneous anaplastic astrocytoma, WHO grade III: T1-weighted MRI after application of Gd-DTPA (A) shows no contrast enhancement. T2-weighted MRI scan (B) shows widespread abnormalities. (C) 18 F-FET-PET identifies a hot spot in the posterior part that cannot be identified on MRI. Biopsy in this area yielded an anaplastic astrocytoma, WHO grade III.

Glioblastoma (WHO grade IV) pretreated by surgery and radiochemotherapy. T1-weighted MRI after application of Gd-DTPA (A) and T2-weighted MRI (B) are ambiguous. (C) 18 F-FET PET identifies pathologic tracer accumulation, which was confirmed as tumor recurrence. (Color version of figure is available online.)

Treatment Monitoring

The diagnostic value of MRI and CT concerning changes in tumor size or contrast enhancement in response to therapy is limited because the known reactive transient BBB alterations with consecutive contrast enhancement may mimic tumor progression. This phenomenon, so-called “pseudoprogression,” is seen in 20%-47% of cases and can lead to an unnecessary overtreatment. 84 The feasibility and usefulness of 11 C-MET and 18 F-FET-PET for therapy assessment and follow-up after surgery, chemotherapy, and radiotherapy have been demonstrated in several studies. The currently available data suggest that a reduction of amino acid uptake by a glioma is a sign of a response to treatment. Recently, a prospective study evaluated the prognostic value of early changes of 18 F-FET uptake after postoperative radiochemotherapy in glioblastomas. 85 It could be demonstrated that PET responders with a decrease of the tumor/brain ratio of 㸐% had a significantly longer disease-free survival and overall survival (OS) than patients with stable or increasing tracer uptake after radiochemotherapy in glioblastomas. A reliable monitoring of chemotherapy could also be demonstrated with 11 C-MET and 18 F-FET-PET in recurrent glioblastoma during standard chemotherapy with TMZ, 86,87 as well as in some experimental therapeutic approaches, such as radioimmunotherapy, convection-enhanced delivery of paclitaxel, and chemotherapy with bevacizumab and irinotecan. 88-90 The cutoff values of the tumor/brain ratio of IMT, MET, and FET uptake on the different clinical questions in the literature are summarized in Table 2 .

Table 2

Quantitative Thresholds for Imaging Gliomas With Amino Acid Tracers

TracerClinical QuestionCutoffMethodReference
IMTGlioma vs non-neoplastic lesion1.78Tumor/brain ratio a 52
Recurrent glioma vs radionecrosis1.8Tumor/brain ratio a 22
METGlioma vs non-neoplastic lesion1.47Mean tumor/brain ratio50
Glioma vs peritumoral tissue1.3Mean tumor/brain ratio56
Recurrent glioma vs radionecrosis2.2Maximum tumor/brain ratio17
FETGlioma vs peritumoral tissue1.6Mean tumor/brain ratio58
Recurrent glioma vs radionecrosis2.0Maximum tumor/brain ratio21
Therapy assessmentDecrease 㸐%Maximum tumor/brain ratio85

Imaging Brain Tumors in Children

The histologic subtypes of brain tumors in children differ considerably from that in adults. Only few mainly retrospective studies have been performed in children with brain tumors. In children, the determination of tumor grade with amino acids seems to be even less reliable than in adults. A broad overlap of amino acid uptake is observed in low-grade and high-grade tumors. 91 Similar to glucose metabolism, amino acid uptake may be high in low-grade tumors such as pilocytic astrocytomas and gangliogliomas uptake may be relatively low in the highly aggressive medulloblastomas (WHO grade IV), a common diagnosis in infratentorial brain tumors. 92 The potential of amino acids to determine the site of stereotactic biopsy or for image-guided surgical resection of infiltrative low-grade brain tumors in children has been reported. 93 The presence of amino acid uptake after surgery indicates residual tumor in case of ambiguous findings in early postoperative MRI. 94


Results

Tumor-reactive TC in BM correlate with a reduced cancer mortality risk

From 181 of 207 study patients, clinicopathologic classification was obtained (Supplementary Table 1). None of the patients had received neoadjuvant treatment. BM was taken from 123 primary operated, nonmetastasized breast cancer patients during tumor resection. We determined the presence of functional tumor-reactive type-1 TC by IFN-γ ELISPOT assays. As test antigens, we used HLA-A*0201–restricted epitopes from breast tumor–associated antigens MUC1, Her2/neu, MAGE-2, prostate-specific antigen, BA46, cyclin D1, heparanase (Hepa), bcl-2 or p53 ( 4, 13– 22), lysates from autologous breast tumor tissue ( 4), or lysate from the allogeneic breast tumor cell line MCF7 ( 4). Tumor cell–derived antigens efficiently restimulate a broad repertoire of preexisting, tumor-specific T-Helper and cytotoxic TC ( 25). Autologous DC loaded with respective antigens were used for restimulation of ex vivo isolated BMTC during 40 h ELISPOT-assays. According to our previous findings within this short stimulation period, antigen-specific IFN-γ is exclusively secreted by preexisting memory TC ( 26). TC stimulated with irrelevant control antigens served for determination of the unspecific background. As control antigens served an HLA-A*0201–restricted epitope of HIVgag, lysate of autologous PBMC, and lysate of the allogeneic leukemia cell line U937 ( 4). Exemplary IFN-γ ELISPOT data are shown in Fig. 1A. Antigen-specific responses, defined by a significantly increased spot number in triplicate test wells compared with corresponding control wells, are indicated by asterisks.

Detection of tumor-specific immune responses. A, IFN-γ ELISPOT assays with BMTC from exemplary patients using as test antigens (black columns) HLA-A2–restricted tumor peptides (top), autologous tumor or skin lysate (bottom left), or allogeneic breast tumor lysate (MaCa bottom right) compared with respective negative control antigens from HIV or insulin, autologous PBMC lysate (PB-L), or U937 lysate (Leuk white columns). Columns, means of triplicate wells bars, SEM. *, significant (P < 0.05) difference to negative control wells by two-sided Student's t test. Hepa, heparanase. B, mean IFN-γ spots in test and control wells of ELISPOT-positive and ELISPOT-negative patients. TAA, HLA-restricted tumor peptides TU-L, autologous tumor lysate PB-L, autologous PBMC-lysate Leuk, allogeneic U937 leukemia lysate MaCa, allogeneic MCF7 breast cancer cell lysate. P, statistical difference between test groups from positive patients and indicated control groups. C, representative ELISA results from two breast cancer patients demonstrating the presence (positive patient, left) or absence (negative patient, right) of MUC1-specific IgG. OD, absorbance *, significant differences as determined by two-sided Student's t test.

To verify that observed tumor-specific TC responses were not caused by unspecific decreases or increases of IFN-γ spots in control wells, we compared with total spots in responding and nonresponding patients. IFN-γ spots were similar in control and test wells of nonresponding patients, whereas test wells of responding patients showed significantly increased IFN-γ spots compared with the other groups ( Fig. 1B).

TA-reactive TC were detected in 17 of 32 patients (53%) for HLA-A* 0201 –restricted peptides and highly individual with regard to antigen specificity. This is in accordance to a previous study ( 27) and might be due to individual differences in the expression rate of respective TAs. We detected TC reactivity against autologous tumor antigens in 19 of 58 patients (33%) and TC reactivity against allogeneic breast TAs in 19 of 33 patients (58% Supplementary Fig. S1). In total, 55 of 123 patients (45%) showed the presence of tumor-reactive type-1 BMTC. TC reactivity against TAs was significantly increased in BM of patients compared with that of 19 healthy females either with regard to the proportions of responding individuals (45% versus 21%, P = 0.03) and to the proportions of positive test results (Supplementary Figs. S1 and S2).

Breast tumor–specific IgM and IgG responses were analyzed by ELISA, using synthetic peptide MUC1tr(137-157)5 as test and HIVgag as negative control antigen. Presence of MUC1-specific antibodies was assumed in case of significant differences in antibody binding between test and control triplicate wells. Representative results of patients with and without MUC1-specific IgG antibodies are shown in Fig. 1C. Thirty-one of 59 patients (53%) contained MUC1-specific IgG or MUCI-specific IgM antibodies (Supplementary Fig. S1). Ninety percent of them (28 of 59) were of IgM isotype, and 42% (13 of 59) were of IgG isotype. In contrast, we detected in sera of 11 healthy females no MUC1-specific IgG and MUC1-specific IgM in only 2 cases (18%, P < 0.05 Supplementary Fig. S1).

We used the prognosis algorithm ADJUVANT! 8 ( 23) to compare antitumor immune responses with the estimated cancer-related mortality. Patients with tumor-reactive TC had a reduced mortality risk (HLA-A2 peptides, P = 0.006 tumor lysates, P = 0.046 Fig. 2A and B). In contrast, patients with MUC1-specific antibodies had the tendency for a higher risk of cancer-related mortality ( Fig. 2C, n.s.).

Correlation of TC immunity and estimated cancer mortality. Reduced breast cancer mortality risk for patients with TC responses against tumor cell lysate (A, +, light gray column) or HLA-A*0201–restricted tumor peptides (B, +, light gray column) compared with TC-negative patients (A and B, −, dark gray columns). C, the mortality risk was not correlated with the presence (+ light gray column) or absence ( dark gray column) of MUC1-specific antibodies. Columns, mean bars, SEM. *, significant difference, P < 0.05 two-sided Student's t test. n.s., not significant.

Tumor-specific immune responses correlate with tumor pathobiology

We performed a subgroup analysis of clinicopathologic parameters to identify prognostic factors that correlated with spontaneous immune responses. TC reactivity was not correlated with the major prognostic factors, tumor size, lymph node involvement, or tumor stage ( Fig. 3A), but instead with a high to moderate tumor cell differentiation, hormone receptor expression and low proliferative activity (P = 0.05, P = 0.02, P = 0.05, respectively Fig. 3B). Because HER-2 is a prognostic factor in breast cancer and a target of tumor immune responses, we also evaluated a potential correlation of Her-2 expression with antitumor reactivity. In our study group, 24 among 176 patients were Her-2 positive and 152 were Her-2 negative by immunohistochemistry and/or fluorescence in situ hybridization analysis (data not shown). We detected tumor-specific TC in 25% of patients with Her-2–positive but in 42% of Her-2–negative patients (not significant).

Antitumor immunity and clinicopathologic features. A, proportions of patients with tumor-specific TC (left) or antibodies (right) according to tumor size (T), lymph node involvement (N), stage (St.), and age (< or >60 y). B and C, correlation of TC responses with pathobiological features. Proportions of patients containing tumor-reactive TC (left) or antibodies (right) according to grade (G), ER expression, or proliferative activity (% Ki67+ tumor cells B), or stratified into groups combining high tumor differentiation (G1,2) with ER expression (ER+) or low tumor differentiation (G3) and lack of ER expression (ER− C). D, dichotomy of antitumor TC and antihumoral immune responses. Proportions of patients containing MUC1-specific antibodies according to the presence (+) or absence (−) of tumor-reactive TC. *, significant differences by χ 2 test (AC) or Fisher's exact test (D) n, number of patients.

In contrast to TC responses, MUC1-specific antibodies correlated with increased tumor size and stage (P = 0.005 and P = 0.03, respectively, Fig. 3A) and were predominantly detectable in patients with lowly differentiated and receptor-negative tumors (not significant Fig. 3B). These findings show that spontaneous tumor-specific TC responses correlate with a certain tumor cell phenotype rather than with tumor size or tumor cell presence in the lymphoid system. Accordingly, the rate of TC responses against HLA-A2–restricted tumor peptides or tumor lysate was strongly increased in patients with well-differentiated and ER-positive tumors (78% and 63%, respectively) when compared with patients with poorly differentiated, hormone receptor–negative tumors (16%, P = 0.05 and 5%, P = 0.004, respectively). In contrast, humoral responses were decreased in the former group of patients (19%, not significant Fig. 3C). A majority of 70% of patients without TA-reactive TC showed instead TA-specific antibodies, whereas only few patients (21%) with a tumor-specific type-1 BMTC response contained TA-specific antibodies (P = 0.03 Fig. 3D).

Tumor pathobiology determines the functional capacity of TA-specific CD8+TC lines

The observed lack of TA-specific type-1 TC reactivity in patients with high-grade tumors could be explained by reduced numbers of TA-specific TC in these patients. Alternatively, such TC might have remained undetected in IFN-γ ELISPOT assay due to functional blockade. We therefore compared the numbers of Her-2/neu–specific CD8+TC by flowcytometry using Her-2/neu–loaded HLA-A*0201 tetramers. As shown in Fig. 4A, the frequencies of Her-2/neu–specific TC were increased in poorly differentiated tumors. Thus, reduced frequencies of TA-specific TC did not account for the observed lack of type-1 TC responses in patients with high-grade tumors. We therefore established Her-2/neu–specific CD8 TC lines from BM of 12 different HLA-A2+ breast cancer patients. TC lines were established by repeated isolation of antigen-specific cells with magnetic beads coupled to Her-2/neu-peptide–loaded HLA-A2 complexes ( 28) and subsequent polyclonal expansion of the cells. We used as antigen-presenting cells in subsequent functional assays T2 cells loaded with a defined high amount of Her-2 peptide (20 μg/mL) to reduce the risk that insufficient TCR signaling (caused by different TCR avidities among the TC lines) accounted for putative functional differences. The TC lines were tested for their capacity to lyse Her-2/neu–loaded HLA-A2+ T2 target cells and/or to secrete IFN-γ upon specific stimulation. None of the TC lines were derived from patients with Her-2/neu overexpression. Figure 4B shows for one representative TC line the proportion of Her-2/neu–specific TC, its capacity to lyse Her-2–loaded target cells and to secrete IFN-γ in response to antigen-specific stimulation. In total, six TC lines showed functional capacity, whereas six were tolerant ( Fig. 4C). Four of six lines from patients with low-grade tumors, and five of six lines from hormone receptor–positive patients showed functional capacity, whereas all six TC lines from patients with high-grade or hormone receptor–negative tumors were tolerant (P = 0.03 and P = 0.01, respectively Fig. 4D).

Functional tolerance of tumor-specific TC in patients with high-grade ER breast tumors. A, mean + SD proportions of Her-2.tetramer–binding CD8+TC in patients with breast carcinomas of high (G1), intermediate (G2), or low (G3) differentiation. One exemplary tetramer staining is shown. B, left, proportion of Her-2/neu–specific CD8+TC after antigen-specific isolation and expansion and corresponding Her-2/neu–specific TC function analyzed by ELISPOT assay (middle) and 4-h chromium-release assay (right) using selected, Her-2/neu–specific CD8+TC (black columns) or unselected TC (gray columns) as responder cells and Her-2/neu-, HIV-, or insulin (Ins)-loaded T2 cells as target cells. C, Her-2/neu–specific lysis (black columns) and/or Her-2–specific IFN-γ secreting TC (gray columns) in Her-2/neu–specific TC lines according to differentiation (G) of respective primary tumors. D, correlation of functional reactivity (pos. gray columns) or tolerance (neg. white columns) of Her-2/neu–specific CD8+TC lines from 12 patients with high/moderate differentiation and/or ER expression of corresponding tumors. *, significant difference, by Student's t test (A and B) or Fisher's exact test (D) n, number of different patients tested.

Intratumoral cytokine patterns correlate with systemic tumor immune responses and tumor pathobiology

To assess potential reasons for the observed correlation of tumor pathobiology with systemic tumor-specific immune responses, we determined in lysates from 36 tumors the concentrations of 27 immune-modulatory cytokines, chemokines, and growth factors (Supplementary Table S2) by multiplex analysis. The results were statistically compared with the calculated frequencies of TA-reactive TC. These were calculated in positive samples by subtracting mean IFN-γ spots in negative control wells from mean spots in test wells. Figure 5A shows a heat map analysis of the cumulative results. Among all tested factors, only IFN-α was positively associated with increased TC responses, whereas intratumoral TGFβ1 was correlated with reduced TC frequencies. We also evaluated the presence or absence of tumor-reactive BMTC or MUC1-specific antibodies according to intratumoral expression of IFN-α and TGFβ1. Seventy-eight percent of patients with tumors containing TGFβ1 levels below the median concentration of 176 pg/mL together with detectable amounts (>0.1 pg/mL) of IFN-α, but only 21% of patients with increased intratumoral TGFβ1 and undetectable IFN-α showed the presence of tumor-reactive BMTC (P = 0.003 Fig. 5B). In contrast, MUC1-specific antibody responses were highly correlated with increased TGFβ1 and absence of IFN-α (P = 0.009 Supplementary Fig. S1 Fig. 5B). Accordingly, IFN-α was significantly increased in tumors of patients with TC responses, whereas increased TGFβ1 correlated with reduced frequencies of tumor-reactive TC ( Fig. 5C). Importantly, the concentrations of both cytokines in tumor tissue showed no correlation to the respective cytokine levels in corresponding PB samples (Supplementary Figs. S2 and S3). Thus, the local contents of TGFβ1 and IFN-α in breast tumor tissues were inversely correlated with the presence and frequencies of systemic tumor-reactive TC or tumor-specific antibodies.

Correlation of systemic antitumor immune responses and cytokine content in breast carcinomas. A, heat map analysis of mean cytokine concentrations in 36 breast tumors and corresponding frequencies of tumor-reactive BMTC. B, proportion of patients containing (black columns) or lacking (white columns) tumor-reactive TC (left) or MUC1-specific antibodies (right) in patient groups characterized by TGFβ1 increased above the median value and undetectable IFN-α or reduced TGFβ1 and detectable IFN-α. *, significant difference (left, χ 2 test right, Fisher's exact test). C, left, presence of tumor-reactive TC correlates with increased intratumoral IFN-α. *, significant difference (two-sided Student's t test). Middle graph, reduced frequencies of tumor-reactive TC correlate with increased TGFβ1 levels above the median of the whole group. Columns, mean frequencies bars, SD. *, significant difference (χ 2 test). Right graph, Spearman's rank correlation demonstrating a significant inverse correlation between TGFβ1 contents in primary breast tumors and frequencies of tumor-reactive TC. D, concentrations of IFN-α (left), TGFβ1 (middle), or of IFN-α and TGFβ1 (right) in tumor lysates from 51 primary breast tumor tissues or in lysates of normal breast tissue (donors) determined by ELISA. Dots, different patients or donors. *, significant difference (two-sided Student's t test).

IFN-α was increased in tumors of patients with well differentiated (G1/2) primary breast tumors (P = 0.03 Fig. 5D) compared with normal breast tissue and poorly differentiated (G3) breast tumors. In contrast, TGFβ1 was enhanced in poorly differentiated (G3) tumors (P = 0.04). Accordingly, the expression patterns of IFN-α and TGFβ1 in 51 primary breast tumors revealed two major subgroups containing either high levels of IFN-α together with low concentrations of TGFβ1, or the opposite pattern ( Fig. 5D).

TGFβ1 and IFN-α influence priming of tumor-specific TC responses in vitro

We hypothesized that TGFβ1 and IFN-α in the tumor environment regulate systemic immunity by influences on immature DC (iDC) during antigen uptake. In this case, their respective concentrations should be sufficient to modify the capacity of iDC to prime type-1 TC responses. We therefore generated iDC from patients and pulsed them with autologous tumor lysate or with the synthetic long peptide MUC1tr(137-157)5 ( 7) for 18 hours in the presence or absence of 20 pg/mL IFN-α or 200 pg/mL TGFβ1 at concentrations detectable in breast tumors. DC were then carefully washed and cocultured with separated autologous naïve (CD45RO − ) or memory (CD45RA − ) TC for 7 days. Priming of tumor-reactive TC was then evaluated by IFN-γ ELISPOT-assay. Representative results of two independent experiments are shown in Fig. 6A and B. In 3 of 11 cases, we detected an induction of tumor-reactive TC only when DC had been pretreated with IFN-α ( Fig. 6A and C). Seven of 18 cultures spontaneously contained tumor-reactive effector TC ( Fig. 6D). In six of these cases, TGFβ pretreatment inhibited the capacity of DC to prime tumor-reactive TC ( Fig. 6B and D). DC-pretreatment with neither TGFβ1 nor IFN-α had no effect on memory TC of the same patients (data not shown). These findings indicate that IFN-α and TGFβ1 are present in breast carcinomas at sufficient amounts to regulate the capacity of iDC to induce primary TA-specific TC.

TGFβ1 and IFN-α influence priming of tumor-specific TC. Isolated naïve TC were stimulated for 7 d with TA-pulsed DC (black columns). In some cases, DC were coincubated during antigen uptake with 20 pg/mL IFN-α (A and C) or 200 pg/mL TGFβ1 (B and D). After 7 d, TCs were tested by IFN-γ ELISPOT assay for reactivity against TAs (MUC1tr(137-157)5 or autologous tumor cell lysate (black and dark gray columns) or corresponding negative control antigens (huIgG or autologous PB-lysate white or light gray columns). A and B, representative experiments show TC priming by pretreatment of DC with IFN-α (A) or abrogation of TC priming by DC pretreatment with TGFβ1 (B). C, cumulative frequencies of tumor-reactive TC induced by antigen-pulsed DC pretreated with IFN-α. D, cumulative frequencies of tumor-reactive TC induced by TA-pulsed DC pretreated with TGFβ1. Dots, samples of different patients. Dashed lines, connect samples from the same patients. Horizontal full lines, the mean frequencies of tumor-reactive TC. *, significant difference (two-sided Student's t test).


How Vaccines Work

Claire-Anne Siegrist MD , Paul-Henri Lambert MD , in The Vaccine Book (Second Edition) , 2016

9 Vaccine-induced T-cell memory

T-cell memory is a critical component of immune responses to intracellular pathogens. Following the antigen-driven expansion and the death of effector cells after antigen clearance, some of the remaining T cells differentiate into memory T cells of two different types: central memory and effector memory T cells. 24 The first ones are located in lymphoid organs and bone marrow and have a high proliferative potential whereas the second ones stay in peripheral tissues in a preactivated form that enables them with immediate action on pathogen recognition. A third type of memory T cells (resident memory cells) was recently recognized as memory T cells which remain settled within specific organs such as the intestine, the lungs, and the skin. They appear important for the protection against mucosal infections. 25

It is useful to know that the establishment of T-cell memory requires some time after the initial priming. Secondary T-cell responses are lower if vaccine boosters are given too early. Through homeostatic proliferation, memory T cells may persist lifelong, even without antigen exposure. 26

A number of T-cell parameters can be measured during vaccine studies. Some are quantitative for example, measurement of T-cell proliferation following antigen stimulation with a dye and quantification of T-cell frequencies by ELISPOT or flow cytometry. Some assays add a functional component, for example, assessment of the production of cytokines by ELISPOT or flow cytometry, or cytotoxic assays.


Prevalence of Syndecan-1 (CD138) Expression in Different Kinds of Human Tumors and Normal Tissues

Syndecan-1 (CD138) is a transmembrane proteoglycan known to be expressed in various normal and malignant tissues. It is of interest because of a possible prognostic role of differential expression in tumors and its role as a target for indatuximab, a monoclonal antibody coupled with a cytotoxic agent. To comprehensively analyze CD138 in normal and neoplastic tissues, we used tissue microarrays (TMAs) for analyzing immunohistochemically detectable CD138 expression in 2,518 tissue samples from 85 different tumor entities and 76 different normal tissue types. The data showed that CD138 expression is abundant in tumors. At least an occasional weak CD138 immunostaining could be detected in 71 of 82 (87%) different tumor types, and 58 entities (71%) had at least one tumor with a strong positivity. In normal tissues, a particularly strong expression was found in normal squamous epithelium of various organs, goblet and columnar cells of the gastrointestinal tract, and in hepatocytes. The highly standardized analysis of most human cancer types resulted in a ranking order of tumors according to the frequency and levels of CD138 expression. CD138 immunostaining was highest in squamous cell carcinomas such as from the esophagus (100%), cervix uteri (79.5%), lung (85.7%), vagina (89.7%) or vulva (73.3%), and in invasive urothelial cancer (76.2%). In adenocarcinomas, CD138 was also high in lung (82.9%) and colorectal cancer (85.3%) but often lower in pancreas (73.3%), stomach (54.2% in intestinal type), or prostate carcinomas (16.3%). CD138 expression was usually low or absent in germ cell tumors, sarcomas, endocrine tumors including thyroid cancer, and neuroendocrine tumors. In summary, the preferential expression in squamous cell carcinomas of various sites makes these cancers prime targets for anti-CD138 treatments once these might become available. Abundant expression in many different normal tissues might pose obstacles to exploiting CD138 as a therapeutic target, however.

1. Introduction

Syndecan-1 (CD138) is one of four members of the syndecan family. It is a cell surface protein consisting of three structural domains, one of which is extracellular and binds heparin sulfates and chondroitin sulfates [1]. Syndecan-1 has relevance for cell-cell and cell-matrix interactions [1]. It is involved in the regulation of cell proliferation, migration, and the organization of the cytoskeleton [1]. In normal tissues, CD138 is known to be expressed on plasma cells and various epithelial cell types.

CD138 expression in cancer is of potential clinical interest as specific drugs targeting CD138 are currently being evaluated in clinical trials. In a phase II trial on plasmocytoma, clinical efficacy and low side effects have been reported [2, 3]. In preclinical studies, these antibodies also showed efficacy against triple negative breast cancer and melanoma [4, 5]. If anti-CD138 therapies should prove successful, other CD138-positive cancer types might as well benefit from such treatments.

Altered CD138 expression has been described in various malignant tumors. For example, overexpression of CD138 has been reported in breast, urinary bladder, gallbladder, pancreatic, ovarian, endometrial, and prostate cancer [1]. In other cancer types, such as lung, head/neck, gastric, renal, and colorectal cancer, CD138 expression was found to be reduced as compared to adjacent normal epithelium [1]. In several of these tumor types, either reduced or increased CD138 expression was linked to unfavorable tumor phenotype and poor patient prognosis [6–9]. Previous studies on CD138 in cancer have applied various different reagents and protocols for their immunohistochemical staining. It is probably because of this that the existing literature is highly discrepant with respect to the prevalence of CD138 expression in different tumor types. For example, the range of the reported CD138 positivity ranges from 26% [10] to 100% [11] in urinary bladder cancer, from 23% [10] to 89% [12] in squamous lung cancer, from 33% [13] to 100% [14] in breast cancer, from 50.5% [15] to 87% [10] in squamous cell carcinoma of the esophagus, and from 24.7% [16] to 89.7% [17] in squamous cell carcinoma of the cervix.

Given these heterogeneous data, the existing literature does not easily allow to determine these cancer types, where CD138 plays a particularly important role. To compare the prevalence and intensity of CD138 expression between tumor entities and to identify these cancer types that might be optimal candidates for anti-CD138 drugs, we thus analyzed more than 2500 cancers and 76 normal tissues using one standard protocol. For this purpose, a multitumor tissue microarray (TMA) was used containing up to 50 different tumors from 85 different tumor types and subtypes. The results of our study identify a broad range of highly CD138-expressing tumor entities.

2. Materials and Methods

2.1. Tissue Microarrays (TMAs)

We used two different sets of preexisting TMAs to study CD138 expression in normal human and cancerous human tissues. The first TMA was composed of one sample of 76 different normal tissue types (608 samples on one slide). The second TMA contained a total of 3,642 primary tumors from 85 tumor types and subtypes. The samples were distributed among 7 different TMA blocks (containing between 414 and 522 samples). The composition of the TMA is described in Table 1 in Results. All samples were derived from the archives of the Institute of Pathology, University Hospital of Hamburg (Hamburg, Germany). Each TMA block contains an identical standard control section with 40 normal and tumor tissue spots in order to control for possible slide-to-slide variability of the immunostaining. Tissues were fixed in 4% buffered formalin and then embedded in paraffin. TMA tissue spot diameter was 0.6 mm. All works were compliant with the Helsinki Declaration. Informed consent was not necessary.

2.2. Immunohistochemistry

Freshly cut TMA sections were immunostained on one day and in one experiment. Slides were deparaffinized and exposed to heat-induced antigen retrieval for 5 minutes in an autoclave at 121°C in pH 9 Dako Target Retrieval Solution buffer. Primary antibody specific for total Syndecan-1 (mouse monoclonal antibody, clone JASY1, Dianova, Hamburg, Germany, dilution 1 : 200) was applied at 37°C for 60 minutes. Bound antibody was then visualized using the EnVision Kit (Dako, Glostrup, Denmark) according to the manufacturer’s directions. For tumor tissues, the percentage of positive epithelial cells was estimated and the staining intensity was semiquantitatively recorded (0, 1+, 2+, and 3+). For statistical analyses, the staining results were categorized into four groups. Tumors without any staining were considered as negative. Tumors with 1+ staining intensity in ≤70% of cells and 2+ intensity in ≤30% of cells were considered weakly positive. Tumors with 1+ staining intensity in >70% of cells, 2+ intensity in 30% to 70%, or 3+ intensity in ≤30% were considered moderately positive. Tumors with 2+ intensity in >70% or 3+ intensity in >30% of cells were considered strongly positive. These categories represent standard cutoffs that others and us have used in numerous IHC studies [18].

3. Results

3.1. Technical Issues

A total of 2,518 (69%) of the 3,642 tumor tissue samples were interpretable in our TMA analysis. Reasons for analysis failure included a fraction of missing samples or samples lacking unequivocal tumor cells. A sufficient number of samples were analyzable for all 76 normal tissue types enabling a complete normal tissue evaluation.

3.2. Syndecan-1 in Normal Tissues

All positive CD138 immunostainings in normal tissues are summarized in Table 2. CD138 was abundantly expressed, mostly in various epithelial cell types. A particularly strong expression of CD138 was observed in squamous epithelial cells of various organs (Figure 1(a)), goblet cells of the gastrointestinal tract (Figure 1(b)), columnar cells in the gall bladder (Figure 1(c)), and hepatocytes (Figure 1(d)). No CD138 staining was detected in the following tissues: aorta/intima, aorta/media, heart (left ventricle), skeletal muscle, skeletal muscle/tongue, myometrium, muscular wall appendix, esophagus, stomach, ileum, colon descendens, kidney pelvis and urinary bladder, penis (glans/corpus spongiosum), ovary (stroma), fat tissue (white), spleen, thymus, ovary (corpus luteum), ovary (follicular cyst), thyroid, cerebellum, cerebrum, pituitary gland (posterior lobe), pituitary gland (anterior lobe), and bone marrow.


11.1. CARCINOMA

Carcinoma in dogs and cats is characterized by different stromal reactions depending on the subject. A simpler classification that can allow histopathologists to establish rapid diagnosis and, to a certain extent, prediction, includes in the group of epithelial tumors: papillary, tubular, solid and anaplastic carcinomas. Precancerous lobules and ductal hyperplasia are found at the periphery of carcinogenic nodules, in adjacent tissues, in both dogs (73.6%) and cats (56.3%) [4].

Macroscopically, carcinoma is characterized by rapid growth, doubling its volume in a short time, with local invasion, infiltrating the surrounding normal tissue. Sometimes, mammary neoplasms are delimited, a capsule appearing on palpation, but they present fibrous adhesions to the epidermis and the muscle fasciae or the neighboring muscles, and they cannot be freely moved. The skin is frequently ulcerated and the tumor invades the lymphatic vessels and lymph nodes, skin and the adjacent gland on the same side.

Mammary neoplasms can have diameters between 2 and 20 cm, and round, ovoid, discoid, fungiform or poorly defined shapes. The tumor extends rapidly and occupies the whole gland, as well as adjacent glands, and carcinomas can coexist with benign tumors in the same gland and/or the neighboring glands.

Adenocarcinomas are usually soft, and in section, a diffuse or lobular structure of homogeneous tissue of white-cream color appears. Papillary carcinomas have a firm or soft-bloody structure. Scirrhous carcinomas have irregular shapes, they are poorly delimited and occasionally invade adjacent mammary glands. They are of a dense-ligneous, even hard consistency, white-gray or brown-yellow color, and they adhere to skin or the basic musculature. Solid carcinomas are soft and in section they have a lobular structure, of white or gray color. Squamous cell carcinomas are of irregular shapes, hard, in section their structure is lobular, color being gray or white, with yellow spots [37].

Carcinomas generally develop rapidly, and they are detected by the owner in 2𠄶 months. If, following diagnosis, the mammary tumor is not removed, tumor growth lasts for a longer time before the dog’s death. Carcinomas may develop over a period of 3 months to 6 years. The conclusions drawn by FOWLER et al. (1974), based on a large number of mammary neoplasms in bitches, regarding the behavior of carcinomas after diagnosis and treatment, are extremely interesting. The mean survival time after the diagnosis of infiltrating papillary carcinomas was 5.6 months, less than for other carcinomas. The mean duration after the diagnosis of infiltrating solid carcinoma was 7.3 months. Scirrhous carcinoma had a longer duration than non-scirrhous carcinoma, 9.7 months. Most dogs with infiltrating papillary carcinoma died following metastases. The behavior of scirrhous carcinoma was similar to that of papillary carcinoma.

Epithelial carcinomas may develop from intralobular ductal or alveolar epithelium, appearing as non-infiltrating or infiltrating tumor structures. The evolution duration of non-infiltrating carcinomas was 36 months and that of infiltrating carcinomas 13 months.

Metastases of mammary carcinomas occur in 25% of cases. The metastatic process is facilitated by both blood flow and lymphatic flow, distributed in the mammary parenchyma.

11.1.1. Adenocarcinoma

Simple tubular adenocarcinoma is a relatively frequent tumor in dogs, the tubular type being predominant. The microscopic structure is dominated by tubular epithelial cells, in which pleomorphism and mitotic activity is estimated from low to high, and necrotic foci are frequent. The connective stroma can be in limited or moderate amounts. Tumor proliferation is surrounded by variable lymphocytic infiltration. The histological differentiation between tubular adenocarcinoma and benign lesion forms is difficult. Benign lesions can have in some cases a high mitotic activity or they can stimulate local invasive growth. In cats, these tumors represent the most frequent type. Tubular adenocarcinoma has in 70% of cases an invasive character, or expansive nodular character in 30%. The lymphocytic infiltration of the tumor is frequent, in approximately 50% of cases (Fig. 11.1, 11.2, 11.4, 11.5, 11.6, 11.30).


Evolution of CAR T-Cell Therapies

Other refinements or reconfigurations of CAR T cells are being tested. One approach is the development of CAR T-cell therapies that use immune cells collected not from patients, but from healthy donors. The idea is to create so-called off-the-shelf CAR T-cell therapies that are immediately available for use and don't have to be manufactured for each patient.

The French company Cellectis, in fact, has launched a phase I trial of its off-the-shelf CD19-targeted CAR T-cell product in the United States for patients with advanced acute myeloid leukemia. The company's product—which is made using a gene-editing technology known as TALEN—has already been tested in Europe, including in two infants with ALL who had exhausted all other treatment options. In both cases, the treatment was effective.

Numerous other approaches are under investigation. Researchers, for example, are using nanotechnology to create CAR T cells inside the body, developing CAR T cells with "off switches" as a means of preventing or limiting side effects like CRS, and using the gene-editing technology CRISPR/Cas9 to more precisely engineer the T cells.

But there is still more to do with existing CAR T-cell therapies, Dr. Fry said.

He is particularly enthusiastic about the potential to use CAR T cells earlier in the treatment process for children with ALL, specifically those who are at high risk (based on specific clinical factors) of their disease returning after their initial chemotherapy, which typically is given for approximately 2 and a half years.

In this scenario, he explained, if early indicators suggested that these high-risk patients weren't having an optimal response to chemotherapy, it could be stopped and the patients could be treated with CAR T cells.

For patients who respond well, "they could be spared 2 more years of chemotherapy," Dr. Fry said. "That's amazing to think about."


Affiliations

School of Medicine, Shandong University, 250012, Jinan, People’s Republic of China

Department of Medicine, Center for Molecular Medicine (CMM) and Bioclinicum, Karolinska Institutet and Karolinska University Hospital Solna, 171 64, Solna, Sweden

Department of Oncology-Pathology and Bioclinicum, Karolinska Institutet and Karolinska University Hospital Solna, 171 64, Solna, Sweden

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