Information

How to gauge the clinical significance of specific cell type presence?


How does one decide whether the presence of certain cell types is clinically important or negligible? Would the presence of certain cells in conjunction with other symptoms be enough, or should it be judged on relative proportions?

I have arrived at a diagnosis for a case study (and I know it is correct) and am just reviewing what I have included and am beginning to question myself. I fear that I am making unnecessary tenuous connections to further support my conclusions.

An example, to put this into context:

  • A peripheral blood film has all the hallmarks of acute myeloid leukaemia (AML), however, the film alone is not enough to confirm.
  • In addition, have spotted definitely one, maybe two, dacrocytes (teardrop cell) on the film, these are not typically associated with AML as far as I am aware.
  • Dacryocytes are not diagnostically indicative of any specific condition.
  • Dacrocytes are however present in several conditions that can transform to AML.

So, in this scenario, I feel it would be worth mentioning considering the clinical setting but the numbers just seem so insignificant that I am concerned it would appear as grasping, or a bit through the grapevine.

Any guidance in general is appreciated, I'm not looking for an answer to the provided example per se.


Clinical significance of HRAS and KRAS genes expression in patients with non–small-cell lung cancer - preliminary findings

The RAS family protooncogenes, including KRAS, NRAS and HRAS, encode proteins responsible for the regulation of growth, differentiation and survival of many cell types. The HRAS and KRAS oncogene mutations are well defined, however, the clinical significance of RAS expressions in non–small-cell lung cancer (NSCLC) is still uncertain.

Methods

A total of 39 whole blood samples of NSCLC (the investigated group), collected at three points of time: at the time of diagnosis, 100 days and 1 year after the surgery as well as 35 tissue samples obtained during the surgery were included in this study. HRAS and KRAS genes mRNA expression were assessed using quantitative real-time polymerase chain reaction techniques.

Results

Increased relative HRAS mRNA level in blood was found significantly more frequently in the group of smokers (p = 0.008). Patients with squamous cell carcinoma subtypes of NSCLC were more likely to show an overexpression of HRAS gene in blood, but not statistically significant (p = 0.065). In tumor tissue overexpression of HRAS gene was associated with adenocarcinoma subtype (p = 0.049). No statistically significant associations were found for the expression of KRAS with any clinicopathological parameters, except the age of patients, within the study. There were no differences between the relative HRAS and KRAS genes expression levels in blood samples taken from the same patients during the 3 observation points, as well as between blood collected from patients before surgery and tissue samples obtained during operation.

Conclusion

The potential associations between high HRAS expression levels, age, smoking status and histological type of cancer were observed, which emphasizes the need for further study of the RAS family. Therefore, subsequent research involving larger numbers of patients and a longer follow-up, as well as multicenter study are necessary to confirm our findings.


Background

Despite several major achievements in the field of targeted and immune treatments for advanced non-small cell lung cancer (NSCLC), especially for the adenocarcinoma (AC) subgroup, this disease still represents a leading cause of death in Europe and worldwide [1]. At a molecular level, lung AC has been extensively characterized, but the enormous body of studies has led to the identification of only a subgroup of patients (cumulatively encompassing no more than 25% of cases) who have a molecular profile favorable to the efficacy of targeted therapies (i.e.: those carrying either EGFR mutations, or ALK, ROS1 or RET gene rearrangements) [2, 3]. Therefore, the identification of new molecular alterations and the development and application of related targeted strategies is essential to improve the prognosis of this disease.

The receptor tyrosine kinase-like orphan receptor 1 (ROR1) is an oncofoetal glycoprotein involved in differentiation, proliferation, migration and survival during the intrauterine development. ROR1 belongs to the ROR receptor tyrosine kinase family, the only other known member of which is ROR2, with a 58% amino acid sequence coincidence. The structure of human ROR1 comprises one FZ (frizzled) domain, one Ig-like (immunoglobulin-like) C2-type domain, one kringle domain and one protein kinase domain [4, 5]. ROR1 is normally expressed at high levels during development, becoming repressed in adult tissues. However, a low level of ROR1 expression is seen in adipose tissue and, to a lesser degree, in pancreas, lung and a subset of B cell leukemia [6, 7].

Interestingly, ROR1 may be re-induced during adult carcinogenesis. The expression of ROR1 was reported in numerous blood and solid malignancies, and appears to be involved in the inhibition of apoptosis [8]. In particular, silencing of ROR1 in NSCLC cells disrupts their ability to escape anoikis and anchorage-dependent programmed cell death, and shows decreased primary tumor growth when the cells are transplanted into nude mice. ROR1 seems to induce cell survival through at least two different mechanisms, one is mediated by the interaction with EGFR-Erb-B3 via the PI3K pathway, and the other one is dependent on its kinase activity via the c-SRC pathway [9]. Moreover, a recent study reports that ROR1 enhances lung adenocarcinoma growth by activating the Akt/GSK-3α/β/mTOR signaling cascade [10].

The observations of low or null ROR1 expression levels in normal adult tissues and its high expression levels in several cancer types led investigators to examine a potential functional advantage to cancer development and growth conferred by ROR1 and to explore the use of therapies against ROR1, that should be specific in cancer cells [11,12,13,14,15]. Yamaguchi and colleagues suggested that TTF-1 (thyroid transcription factor-1), a lineage-survival oncogene often expressed in lung AC, induces ROR1 expression, favoring by this mean a pro-survival PI3K-AKT activity, and opposing to the pro-apoptotic p38 signaling. They demonstrated that ROR1 knockdown inhibited lung AC cell lines, proposing that this receptor could represent a valuable therapeutic target in lung cancer patients [16]. Various putative approaches targeting ROR1 have been developed, such as blockage of its tyrosine kinase activity, the use of ROR1 as a surface target of monoclonal antibodies (MoAbs), [17] the use of MoAb-toxin conjugates (immunotoxins) or via chimeric antigen-receptor T-cells (CAR T-cell) [18].

Based on the observations described above, we hypothesized that ROR1 could be overexpressed in a significant proportion of lung ACs and potentially defines a subgroup of patients eligible for ROR1-targeted therapies. In addition, we aimed to assess the role of TTF-1 in the induction of ROR1 expression in human tissue samples. Finally, we looked for correlations of ROR1 and the main clinical and molecular features. .


Types of urinary Casts

Urinary casts can be divided into two main categories : Acellular and Cellular Casts.

Acellular Casts Cellular Casts
Hyaline Casts Red Blood Cell Casts
Granular Casts White Blood Cell Casts
Waxy Casts Bacterial Casts
Fatty Casts Epithelial Cell Casts

Results

Detection of PNH-type granulocytes and RBCs

The flow cytometry we used could reliably detect as little as 0.002% CD11b + CD55 − CD59 − cells within the granulocytes gate, as we previously reported (Figure1).7 When granulocytes and RBCs were examined, the percentage of PNH-type cells detected was generally different for granulocytes and RBCs. In patients with low (0.01%) percentages of PNH-type cells in 2 lineages of cells, PNH-type RBCs were more easily recognized than PNH-type granulocytes because of a distinct cluster of glycophorin A + CD55 − CD59 − cells (Figure 2). Thus, the detection of PNH-type RBCs in addition to PNH-type granulocytes appeared to substantiate a diagnosis of bone marrow failure with a minor PNH-type cell population. Among 68 healthy controls, 26.5% exhibited 1 or 2 CD55 − CD59 − cells per 100 000 granulocytes, and 50.0% exhibited 1 or 2 CD55 − CD59 − cells per 100 000 RBCs. However, there was no healthy control who exhibited 3 or more CD55 − CD59 − cells per 100 000 granulocytes and 100 000 RBCs. To avoid false-positive results, the presence of more than 0.003% CD55 − CD59 − cells in granulocytes and RBCs was arbitrarily defined as an increase in PNH-type cells.

Detection of PNH-type granulocytes and RBCs in peripheral blood of RA patients.

Histograms of 3 RA patients exhibiting less than 0.1% CD55 − CD59 − cells are shown. A indicates patient 7 B, patient 12 C, patient 16. Each number represents a percentage of PNH-type cells.

Detection of PNH-type granulocytes and RBCs in peripheral blood of RA patients.

Histograms of 3 RA patients exhibiting less than 0.1% CD55 − CD59 − cells are shown. A indicates patient 7 B, patient 12 C, patient 16. Each number represents a percentage of PNH-type cells.

PIG-A gene abnormalities in a minor population of PNH-type granulocytes

A minor population of PNH-type granulocytes was enriched from 5 RA patients by aerolysin treatment, and all exons of the PIG-Agene in these granulocytes were examined using heteroduplex analysis followed by subcloning and sequencing. Table1 summarizes abnormalities of thePIG-A gene in each patient. Although the proportions of PNH-type cells in these patients were low (0.56 to 2.41%), various abnormalities were detected in all patients.

PIG-A mutations in PNH + RA patients

Patient . Age, y/sex . Exon . Mutations . Position . Consequence .
1 40/M 4 1-bp deletion (T) 998 Frameshift, stop codon in 1002
2 48/M 5 1-bp insertion (T) 1219 Frameshift, stop codon in 1244
4 Point mutation (A to T) 962 Stop codon in 962
4 1-bp deletion (T) 952 Frameshift, stop codon in 953
3 68/F 5 1-bp insertion (T) 1219 Frameshift, stop codon in 1244
4 39/F 4 1-bp deletion (C) 961 Frameshift, stop codon in 981
5 40/F 5 1-bp deletion (G) 1393 Frameshift, stop codon in 1392
Patient . Age, y/sex . Exon . Mutations . Position . Consequence .
1 40/M 4 1-bp deletion (T) 998 Frameshift, stop codon in 1002
2 48/M 5 1-bp insertion (T) 1219 Frameshift, stop codon in 1244
4 Point mutation (A to T) 962 Stop codon in 962
4 1-bp deletion (T) 952 Frameshift, stop codon in 953
3 68/F 5 1-bp insertion (T) 1219 Frameshift, stop codon in 1244
4 39/F 4 1-bp deletion (C) 961 Frameshift, stop codon in 981
5 40/F 5 1-bp deletion (G) 1393 Frameshift, stop codon in 1392

Prevalence of patients with increased PNH-type blood cells among patients with MDS

A significant increase of PNH-type cells was detected in 21 of 119 (17.6%) RA patients. In contrast, increased PNH-type cells were not detected in any of the 4 RARS, 33 RAEB, or 8 RAEB-t patients. Table2 summarizes the clinical data on the 21 PNH + RA patients. Bone marrow aspirates from the sternum were hypercellular or normocellular in most patients, though bone marrow biopsy from the iliac bone marrow showed hypocellularity in 10 of 14 patients tested. The percentage of PNH-type granulocytes varied from 0.003% to 2.41% and was less than 1.0% in 17 of 21 (81.0%) PNH + patients. These low percentages would have been considered insignificant in previous studies. All samples of PNH + RA patients who exhibited less than 0.01% PNH-type cells were reexamined within 1 month and gave similar results. Nine patients did not require treatment because their pancytopenia remained stable or improved spontaneously. The other 12 patients were treated with cyclosporine or anabolic steroids, and all of them, except patients 3 and 9, improved.

Characteristics of PNH + RA patients

Patient . Age, y/sex . Time from
diagnosis, mo .
WBC, 10 9 /L . Hb, g/dL . Platelets, 10 9 /L . NCC in the sternum, 10 9 /L . Iliac bone biopsy . PNH-type
granulocytes/
RBCs, % .
Therapy . Response
to therapy .
Presentation of HLA-DR15
(DRB1 allele) .
1 40/M 58 2.6 10.0 30 68 Hypercellular 1.62/2.83 Oxymetholone (+)
2 48/M 14 2 11.9 88 50 NT 0.56/NT (−) NE 1502
3 68/F 26 2.4 7.9 23 207 Normocellular 1.1/4.65 Cyclosporine (−) 1502
4 39/F 2 2.6 7.1 40 73 NT 1.24/1.19 (−) NE
5 40/F 12 2.5 8.1 45 197 NT 2.41/10.01 Cyclosporine (+) 1502
6 77/F 50 3 7.7 31 186 Hypocellular 0.09/0.47 (−) NE 1501/1502
7 73/F 15 2.9 8.7 73 272 Hypocellular 0.004/0.08 (−) NE 1502
8 60/F 122 2.9 7.3 23 110 NT 0.01/0.1 (−) NE 1501
9 68/M 52 3.2 9.3 21 135 Hypocellular 0.08/0.3 Cyclosporine (−) 1502
10 58/F 78 2.9 7.9 67 188 Normocellular 0.12/0.57 (−) NE 1502
11 79/F 36 3.4 7.4 85 207 Normocellular 0.1/0.2 (−) NE 1501
12 69/F 85 3.2 7.9 21 139 Hypocellular 0.003/0.01 Danazol (+) 1502
13 17/F 6 2.1 9.1 19 139 NT 0.26/0.09 Cyclosporine (+) 1501
14 59/M 23 2.9 8.5 6 150 Hypocellular 0.16/0.13 Cyclosporine (+) 1501
15 54/F 1 2.4 8.2 38 222 Hypocellular 0.02/0.1 Cyclosporine (+) 1502
16 51/M 190 3.6 11.5 121 106 Hypocellular 0.04/0.005 (−) NE 1501/1502
17 60/F 1 4.7 5.9 15 53 Hypocellular 0.03/0.37 Methenolone (+) 1501
18 67/F 30 2.5 8.9 40 477 NT 0.45/0.36 (−) NE 1502
19 56/M 41 3.0 8.6 6 399 Normocellular 0.01/0.006 Cyclosporine (+) 1501
20 68/F 3 3.4 7.0 58 240 Hypocellular 0.02/0.01 Cyclosporine (+) 1501
21 58/M 47 2.3 8.0 4 358 NT 0.003/0.16 Cyclosporine (+) 1501
Patient . Age, y/sex . Time from
diagnosis, mo .
WBC, 10 9 /L . Hb, g/dL . Platelets, 10 9 /L . NCC in the sternum, 10 9 /L . Iliac bone biopsy . PNH-type
granulocytes/
RBCs, % .
Therapy . Response
to therapy .
Presentation of HLA-DR15
(DRB1 allele) .
1 40/M 58 2.6 10.0 30 68 Hypercellular 1.62/2.83 Oxymetholone (+)
2 48/M 14 2 11.9 88 50 NT 0.56/NT (−) NE 1502
3 68/F 26 2.4 7.9 23 207 Normocellular 1.1/4.65 Cyclosporine (−) 1502
4 39/F 2 2.6 7.1 40 73 NT 1.24/1.19 (−) NE
5 40/F 12 2.5 8.1 45 197 NT 2.41/10.01 Cyclosporine (+) 1502
6 77/F 50 3 7.7 31 186 Hypocellular 0.09/0.47 (−) NE 1501/1502
7 73/F 15 2.9 8.7 73 272 Hypocellular 0.004/0.08 (−) NE 1502
8 60/F 122 2.9 7.3 23 110 NT 0.01/0.1 (−) NE 1501
9 68/M 52 3.2 9.3 21 135 Hypocellular 0.08/0.3 Cyclosporine (−) 1502
10 58/F 78 2.9 7.9 67 188 Normocellular 0.12/0.57 (−) NE 1502
11 79/F 36 3.4 7.4 85 207 Normocellular 0.1/0.2 (−) NE 1501
12 69/F 85 3.2 7.9 21 139 Hypocellular 0.003/0.01 Danazol (+) 1502
13 17/F 6 2.1 9.1 19 139 NT 0.26/0.09 Cyclosporine (+) 1501
14 59/M 23 2.9 8.5 6 150 Hypocellular 0.16/0.13 Cyclosporine (+) 1501
15 54/F 1 2.4 8.2 38 222 Hypocellular 0.02/0.1 Cyclosporine (+) 1502
16 51/M 190 3.6 11.5 121 106 Hypocellular 0.04/0.005 (−) NE 1501/1502
17 60/F 1 4.7 5.9 15 53 Hypocellular 0.03/0.37 Methenolone (+) 1501
18 67/F 30 2.5 8.9 40 477 NT 0.45/0.36 (−) NE 1502
19 56/M 41 3.0 8.6 6 399 Normocellular 0.01/0.006 Cyclosporine (+) 1501
20 68/F 3 3.4 7.0 58 240 Hypocellular 0.02/0.01 Cyclosporine (+) 1501
21 58/M 47 2.3 8.0 4 358 NT 0.003/0.16 Cyclosporine (+) 1501

White blood cell, hemoglobin, and platelet counts were determined at the time of diagnosis.

NCC indicates nucleated cell count NT, not tested and NE, not evaluable.

Clinical features of PNH + RA patients compared with PNH − RA patients

Laboratory data and treatment outcomes were compared between PNH + RA patients and PNH − RA patients to analyze the clinical significance of the minor population of PNH-type cells. Table 3 summarizes the results of the comparison. Thirty-three percent of PNH − RA patients had various karyotypic abnormalities, such as monosomy 7 and trisomy 8, whereas only 1 of 21 PNH + RA patients had a karyotypic abnormality of 46,XX,t(68)(q15q22) in 11 of 20 dividing cells. When the degree of dysplasia was compared using the percentage of neutrophils with the Pseudo-Pelger-Hüet anomaly in the bone marrow as a marker, PNH + RA patients showed significantly lower percentages of dysplastic neutrophils than PNH − RA patients. The median platelet count (31 × 10 9 /L) in PNH + RA patients was significantly lower than that in PNH − RA patients (91 × 10 9 /LP = .01).

Clinical features of PNH + and PNH − RA patients

. PNH + RA . PNH − RA . P .
Incidence of karyotypic abnormalities (%) 1 of 21 (4.8) 21 of 64 (32.8) .01 3-150
Neutrophils with the Pseudo-Pelger-Hüet anomaly, % (range) 2.0 (0-35.0) 6.0 (0.5-45.2) .02 3-151
Platelet count, 10 9 /L (range) 31 (4-121) 91 (9-126) .01 3-151
Incidence of HLA-DR15 (DRB1 3-150 1501 and DRB1 3-150 1502) (%) 19 of 21 (90.5) 5 of 27 (18.5) <.001 3-150
Response to cyclosporine therapy (%) 7 of 9 (77.8) 0 of 8 (0) .002 3-150
Progression to advanced MDS or AML (%) 0 of 21 (0) 4 of 65 (6.2) .57 3-150
. PNH + RA . PNH − RA . P .
Incidence of karyotypic abnormalities (%) 1 of 21 (4.8) 21 of 64 (32.8) .01 3-150
Neutrophils with the Pseudo-Pelger-Hüet anomaly, % (range) 2.0 (0-35.0) 6.0 (0.5-45.2) .02 3-151
Platelet count, 10 9 /L (range) 31 (4-121) 91 (9-126) .01 3-151
Incidence of HLA-DR15 (DRB1 3-150 1501 and DRB1 3-150 1502) (%) 19 of 21 (90.5) 5 of 27 (18.5) <.001 3-150
Response to cyclosporine therapy (%) 7 of 9 (77.8) 0 of 8 (0) .002 3-150
Progression to advanced MDS or AML (%) 0 of 21 (0) 4 of 65 (6.2) .57 3-150

Progression to advanced disease was observed for 2.5 years.

The most remarkable difference between the 2 groups was the frequency of HLA-DR15, a split antigen of HLA-DR2. Nineteen of 21 (90.5%) PNH + RA patients had HLA-DRB1*1501 or HLA-DRB1*1502, whereas only 5 of 27 (18.5%) PNH − RA patients who were tested for HLA-DRB1 alleles had this DR antigen. The frequencies of HLA-DRB1*1501 (47.6%) and HLA-DRB1*1502 (52.4%) in PNH + RA patients were much higher than in the general Japanese population (6.1% and 8.7%).16

Seventeen RA patients were treated with cyclosporine for more than 3 months after examination of the levels of PNH-type cells. None of the 8 PNH − RA patients improved, whereas 7 of 9 PNH + RA patients responded to the therapy. During the observation period of 2.5 years, 4 RA patients progressed to advanced MDS or acute myeloid leukemia (AML). All 4 patients had been PNH − , and none of the 21 PNH + RA patients underwent such progression.


Abstract

The incidence of prostate-specific antigen (PSA) monitoring has increased in recent years. However, interpretation of the results is often ambiguous and leads to uncertainty for both the patient and the treating physician. Advantages and disadvantages of measuring PSA and possibilities for improved interpretation using the variable PSA quotient are given.

The prostate gland is a chestnut-sized organ that lies directly under the bladder and encloses the upper section of the urethra. It is approximately 20 to 25 g in a young man and 30 g in an older man. During ejaculation, the prostate adds up to 40 g of a milky secretion to the ejaculate, in which prostate-specific antigen (PSA), a protein formed by the prostate gland, is present in high concentrations. 1–3

Prostatic secretions are slightly acidic with a pH around 6.4. The acidity serves to neutralize vaginal alkalinity and prolong the lifespan of spermatozoa. 4 PSA liquefies semen, promoting sperm motility, and serves to dissolve cervical mucus. PSA is present in low concentrations in the blood, but the concentration increases with prostate irritation, prostatic infection, and benign prostatic hyperplasia (BPH).

PSA exists in the blood in two forms. Most PSA in blood is bound to serum proteins, some of which are inhibitors of the serine protease activity of PSA. Further, PSA is also present as free PSA. 5 Total PSA is the sum of both bound and free PSA however, free PSA is measured only if the total PSA is increased. PSA is primarily a tissue-specific marker. From an elevated PSA measurement, it is difficult to differentiate between a benign and malignant transformation of the prostate gland. Distinguishing between the two is where free PSA is useful. Free PSA is more often formed from benign transformations while bound PSA tends to come from malign transformations.

Both tests (free and total PSA) have high accuracy and repeatability. With increasing age, enlargement of the prostate gland is common and, in most cases, is benign. However, it often leads to unpleasant symptoms, such as problems with urination. The lifetime incidence of prostate carcinoma is 8% to 14% for Caucasian men 5 but prostate carcinoma will not be symptomatic in all of these men. Prostate carcinoma is rare in men under age 50 and the average age at diagnosis is 75 years. The risk is greater for men who have relatives with prostate carcinomas. 6 Only about 3% of the men with prostate carcinoma in Europe and in the United States die from this disease. A cure is more often possible if the tumor is recognized at an early stage however, not all prostate carcinomas are aggressive. Some prostate carcinomas grow rapidly and metastasize. If not recognized at an early stage and treated appropriately, aggressive tumors often lead to death. Others grow slowly, remain asymptomatic, and do not extend to other organs. Cancerous prostate tissue usually releases more PSA and more complexed PSA into the blood than normal, healthy tissue does. Thus, an increased PSA may indicate the presence of prostate carcinoma. The higher the PSA concentration in blood, the more likely one is to find tumors that have extended beyond the prostate gland. 7 Today, asymptomatic and aggressive tumor forms can be differentiated most reliable by means of prostatic biopsy and subsequent histopathological investigation of the tissue.

Until recently, PSA was thought to be produced only in the prostate however, using very sensitive methods, PSA has now been found in low concentrations in many other tissues. The PSA molecule is very similar to kallikrein, which is androgen-dependent and produced in epithelial and glandular tissue.


Introduction

Adult T-cell leukemia/lymphoma (ATLL) is a distinct clinical entity characterized by a mature T-cell surface-marker profile, the association with human T-cell leukemia virus type-1 (HTLV-1), and abnormal lymphocytosis with markedly deformed pleomorphic nuclei.1-3 Identification of recurring cytogenetic abnormalities may provide important clues to the elucidation of the pathogenesis of ATLL. Cytogenetic findings and the analysis of their clinical significance are still limited in mature T-cell malignancies compared with those of B-cell malignancies.4-6 Although many cytogenetic studies have been performed,7-16 the cytogenetics of ATLL is complicated by clinical heterogeneity and a plethora of secondary abnormalities. To improve the accurate evaluation of karyotypes and to identify specific chromosomal abnormalities in ATLL, a large number of karyotypes from various laboratories were reviewed by the ATL Karyotype Review Committee 1985 in Japan.17 Several recurring abnormalities such as trisomy 3, 7, and 21 monosomy X in the female loss of a Y in the male translocations involving 14q11 or 14q32 and deletion in 1p, 3q, 5q, 6q, 7p, 9q, 10p, and 13q have been confirmed.17 However, correlation between these and clinical features, as reported in non-Hodgkin lymphoma (NHL),4-6 has not been attempted in ATLL.

This study reports the detailed cytogenetic findings observed in 50 patients with ATLL and correlates them with clinical characteristics.


Discussion

In this study, 13 gene chips were collected and it was found that STIL expression was significantly increased in osteosarcoma. Highly expressed STIL was associated with the ability to distinguish osteosarcoma from non-osteosarcoma samples, and the patients with high STIL expression are associated with a poor prognosis. Additionally, the in vitro experiments revealed that the silencing of STIL could significantly block proliferation, induce apoptosis, and reduce migration and invasion in osteosarcoma cells. Previous research has identified a wide range of molecular markers that can be used for the diagnosis and treatment of various diseases [14,15,16]. Moreover, several molecular markers for osteosarcoma have also been discovered, including MYC, Cyclin E1, and MiR-455-3p, which are all considered to be promising therapeutic targets [17,18,19]. In this study, STIL was found to play a role of a proto-oncogene in osteosarcoma and was significantly involved in the occurrence and development of osteosarcoma. Compared with previous studies, our findings provide new insight into molecular markers and therapeutic targets for osteosarcoma.

STIL was first isolated from T cell chromosomes from T cell acute lymphoblastic leukemia [20]. Early studies that commonly used mice and zebrafish as animal models found that a deletion of the STIL locus was embryonically lethal [21,22,23]. Moreover, STIL mutations in humans can lead to primary hereditary microcephaly and even cancer [24,25,26]. This is the first study to report the overexpression of STIL in osteosarcoma, and demonstrate that silencing STIL inhibits cell proliferation, promotes cell apoptosis, and suppresses invasion and migration capabilities. Kasai et al. found that STIL was able to regulate the Hh signaling pathway through interacting with Sufu and Gli1 to affect cell proliferation [11]. Wu et al. found STIL to be highly expressed in prostate cancer and could regulate the growth of prostate cancer cells through the MAPK/ERK, PI3K/Akt, and AMPK signaling pathways [27]. Furthermore, Rabinowicz et al. reported that the targeted inhibition of highly expressed STIL could significantly improve the efficacy of DNA-damaging drugs for the treatment of ovarian cancer, and suggested that STIL might be a novel therapeutic target [28]. In recent studies, Wang et al. attenuated the IGF-1/PI3K/AKT pathway by knocking out STIL in gastric cancer, which inhibited cellular proliferation and reduced clone formation ability [29]. These results are consistent with our results and provide evidence for the role of STIL as a proto-oncogene.

To further clarify the potential molecular mechanism of STIL in osteosarcoma, we performed a GO and KEGG enrichment analysis on the STIL differentially co-expressed genes, and they were found to be significantly enriched in the cell cycle pathway. The PPI network results also showed that STIL and the hub co-expressed genes were proteins involved in the cell cycle. The above results indicate that STIL and the differentially co-expressed genes may affect the mitosis and cell proliferation of osteosarcoma cells through cell cycle signaling pathways. The cell cycle is known to have an important function in cellular growth and proliferation. Prior studies have reported that miR-671-5p and miR-299-5p target cell cycle regulation and mediate osteosarcoma proliferation [30, 31]. Zhang et al. found that Ludartin induces apoptosis and cell cycle arrest at the G2/M checkpoint through the elevated expression of p21WAF1 in osteosarcoma cells [32]. Cell cycle pathways have also been established to play an important role in other tumors [33,34,35]. As an important factor in the process of mitosis, STIL may participate in the progression of osteosarcoma by regulating the cell cycle.

In the PPI network, we selected six genes (CDK1, CCNB2, CDC20, CCNA2, BUB1, and AURKB) as the core STIL differentially co-expressed genes in osteosarcoma. CDK1 is a gene related to the cell cycle, and its abnormal expression leads to the development of tumors [36]. In the study conducted by Huang et al., microRNA-199a-3p, as a tumor suppressor gene was found to exhibit low expression in osteosarcoma and may interact with highly expressed CDK1 in the development of osteosarcoma [37]. CCNA2 and CCNB2 are members of cyclin family, which are critical for both cellular proliferation and apoptosis. Shekhar et al. found that CCNA2 is the common target of miR-449a and miR-424 in osteosarcoma, which inhibits tumor progression by inhibiting CCNA2 expression [38]. In another study, silencing CDC6 reduced CCNA2 expression and suppressed osteosarcoma cell proliferation and invasion [39]. CDC20 is a gene that regulates the cell cycle, and is reported to be involved in osteosarcoma development by analyzing the gene chip data [40]. Moreover, apcin blocks osteosarcoma cell growth and invasion by reducing the level of CDC20 expression, indicating that CDC20 may represent a potential therapeutic target [41, 42]. In a recent study, CDC20 was found to exhibit high levels of expression in osteosarcoma cisplatin-resistant cell lines, which enhanced the sensitivity of drug-resistant cell lines to cisplatin by knocking out CDC20 [43]. Moreover, studies using bioinformatics analyses have found that RFC4 may interact with BUB1, which may function to promote osteosarcoma occurrence and development of [44]. AURKB is a serine/threonine kinase that has been proposed to stimulate the invasion and proliferation of osteosarcoma through PTK2/PI3K/AKt/NF-κB signaling pathway and VCP [45, 46]. Thus, AURKB inhibitors may also provide a new option for the treatment of osteosarcoma [47]. In our study, we found that these six genes are highly expressed in osteosarcoma. Therefore, these findings suggest that STIL may play a role in osteosarcoma progression through regulation of expression of these identified genes.

Our study is associated with certain limitations: (1) there is a large heterogeneity in our analysis (67 %). Although we attempted to identify the source of heterogeneity through a sensitivity analysis, the results showed that no particular research to be the source of the heterogeneity and (2) although we have demonstrated that STIL functions as a proto-oncogene in osteosarcoma, its potential molecular mechanism requires further verification both in vivo and in vitro.


Conclusion

The concept of precision oncology has as its foundation the ability to detect clinically relevant and actionable tumor-specific changes in a timely fashion. This may be achieved using temporal cfDNA assays to monitor adaptation to therapy and identify actionable mutations. cfDNA-based profiling of cancer patients offers a number of critical advantages for essentially real-time monitoring of a tumor response to therapy in cancer patients. These include integral representations of tumor heterogeneity, ease of sampling, minimal invasiveness and morbidity, and low cost. However, tumor-derived DNA usually constitutes only a small percentage of total cfDNA so the ability to detect rare genome aberrations is an essential requirement for cfDNA analysis pipelines. Another important parameter is the spectrum of genomic changes the technology is capable of detecting. While targeted assays can be fruitful in the clinical setting, sequence-based approaches offer clear advantages in terms of flexibility of coverage and the ability to detect a wide range of aberrations in tumor genomes. This flexibility will be especially important for managing metastasis and resistance to therapy widely recognized to be among the most important problems in cancer management. Resistance to therapy can be driven by a wide range of genomic aberrations such as point mutations and copy number aberrations. Moreover, resistant subclones can constitute a very small proportion of the tumors total clonal population until the selective pressure of therapy leads to their rapid expansion. Clearly, the early detection of resistant clones requires sensitivity to detect such events. However, this requires minimizing noise in the ctDNA analyses and pushing the sensitivity of detection to the theoretical limits imposed by the plasma levels of ctDNA. Recent evidence suggests that the most promising technology for this is based on molecular tagging-based workflows that suppress errors introduced by PCR and sequencing. This approach is limited mainly by the ctDNA sampling efficiency and is straightforward to scale and thus offer enormous potential for monitoring ctDNA in cancer patients and possibly for screening healthy asymptomatic individuals.


4 Conclusion

Plaque disruption and its resulting coronary thrombosis are thought to be the pathophysiological basis of most acute coronary syndromes. Despite our advanced understanding of the biology of the atherosclerotic process, and the many approaches available for treatment, event rates in coronary disease remain high. In the most recent trials involving acute coronary syndromes, the control group incidences of recurrent cardiac events ranged from 10–25% in the first month after randomization [21–25]. Thus, there remains a need for more effective treatment strategies to improve outcome after acute coronary syndromes. As a result, basic research and clinical investigation continue to refine our understanding and treatment approaches to plaque disruption, coronary thrombosis, and the resulting clinical events.