Microsatellite Instability
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John H. Lin ◽  
Suping Chen ◽  
Aparna Pallavajjala ◽  
Liana B. Guedes ◽  
Tamara L. Lotan ◽  

2021 ◽  
Ruixue Lei ◽  
Yanteng Zhao ◽  
Kai Huang ◽  
Qian Wang ◽  
Kangkang Wan ◽  

Abstract BackgroudMethylated SDC2 and TFPI2 are applied frequently for the early detection of colorectal cancer (CRC). However, they often miss some positive samples, which directly affects their sensitivities, and the underlining mechanism is not well known.Methods:CRC samples from TCGA and GEO datasets were divided into three groups, Highmethylation/ High-methylation (HH), High-methylation/Low-methylation (HL), and Lowmethylation/Low-methylation (LL) according to the methylation status of SDC2 and TFPI2 promoters. Variations in age, tumor location, and microsatellite instable were then assessed between the three groups and verified in our custom cohort.ResultsSamples of HL group preferred to derive from left-sided CRCs (P < 0.05). HH samples showed the highest microsatellite instability and mutation load (mean nonsynonymous mutations for HH/HL/LL: 10.55/3.91/7.02, P = 0.0055). Almost all mutations of BRAF, one of the five typical CpG island methylator phenotype (CIMP) related genes, were observed in HH group (HH/HL/LL: 51/0/1, P = 0.018). Besides, older patients were frequently found in HH group. Expression analysis identified 37, 84, and 22 group-specific differentially expressed genes (DEGs) for HH, HL, and LL, respectively. Functional enrichment analysis revealed that HH-specific DEGs were mainly related to transcription regulation, while LL-specific DEGs were enriched in the biological processes of extracellular matrix interaction and cell migration.Conclusions:The three methylation phenotypes identified based on SDC2 and TFPI2 methylation status showed extensive variations in tumor location, patient age, MSI and ECM biology processes, suggesting that these respective sides should be considered when developing new methylation-based biomarkers for CRC detection.

2021 ◽  
Vol 11 ◽  
Jun Li ◽  
Yunhong Xu ◽  
Gang Peng ◽  
Kuikui Zhu ◽  
Zilong Wu ◽  

The incidence of head and neck squamous cell carcinoma (HNSC) is increasing year by year. The nerve is an important component of the tumor microenvironment, which has a wide range of cross-talk with tumor cells and immune cells, especially in highly innervated organs, such as head and neck cancer and pancreatic cancer. However, the role of cancer-nerve cross-talk-related genes (NCCGs) in HNSC is unclear. In our study, we constructed a prognostic model based on genes with prognostic value in NCCGs. We used Pearson’s correlation to analyze the relationship between NCCGs and immune infiltration, microsatellite instability, tumor mutation burden, drug sensitivity, and clinical stage. We used single-cell sequencing data to analyze the expression of genes associated with stage in different cells and explored the possible pathways affected by these genes via gene set enrichment analysis. In the TCGA-HNSC cohort, a total of 23 genes were up- or downregulated compared with normal tissues. GO and KEGG pathway analysis suggested that NCCGs are mainly concentrated in membrane potential regulation, chemical synapse, axon formation, and neuroreceptor-ligand interaction. Ten genes were identified as prognosis genes by Kaplan-Meier plotter and used as candidate genes for LASSO regression. We constructed a seven-gene prognostic model (NTRK1, L1CAM, GRIN3A, CHRNA5, CHRNA6, CHRNB4, CHRND). The model could effectively predict the 1-, 3-, and 5-year survival rates in the TCGA-HNSC cohort, and the effectiveness of the model was verified by external test data. The genes included in the model were significantly correlated with immune infiltration, microsatellite instability, tumor mutation burden, drug sensitivity, and clinical stage. Single-cell sequencing data of HNSC showed that CHRNB4 was mainly expressed in tumor cells, and multiple metabolic pathways were enriched in high CHRNB4 expression tumor cells. In summary, we used comprehensive bioinformatics analysis to construct a prognostic gene model and revealed the potential of NCCGs as therapeutic targets and prognostic biomarkers in HNSC.

Minggui Pan ◽  
Chen Jiang ◽  
Pam Tse ◽  
Ninah Achacoso ◽  
Stacey Alexeeff ◽  

PURPOSE To examine the association of gain-of-function (GOF) and non–gain-of-function (non-GOF) TP53 mutations with prognosis of metastatic right-sided (RCC) versus left-sided colorectal cancer (LCC). METHODS This cohort study included patients with metastatic colorectal cancer (CRC) who had next-generation sequencing performed from November 2017 to January 2021. We defined R175H, R248W, R248Q, R249S, R273H, R273L, and R282W as GOF and all other mutp53 as non-GOF. We used Cox regression modeling to examine the association between GOF and non-GOF mutp53 and overall survival (OS), adjusting for age, sex, ethnicity, performance status, Charlson comorbidity index and receipt of chemotherapy. RESULTS Of total 1,043 patients, 735 had tumors with mutp53 and 308 had wild-type p53 (wtp53). GOF was associated with worse OS than non-GOF mutp53 only in LCC (hazard ratio [HR] = 1.66 [95% CI, 1.20 to 2.29]), but not in RCC (HR = 0.79 [95% CI, 0.49 to 1.26]). Importantly, RCC was associated with worse OS than LCC only in the subset of patients whose CRC carried non-GOF (HR = 1.76 [95% CI, 1.30 to 2.39]), but not GOF mutp53 (HR = 0.92 [95% CI, 0.55 to 1.53]) or wtp53 (HR = 0.88 [95% CI, 0.60 to 1.28]). These associations were largely unchanged after also adjusting for RAS, BRAF, and PIK3CA mutations, and microsatellite instability-high. CONCLUSION Poorer survival of patients with metastatic RCC versus LCC appeared to be restricted to the subset with non-GOF mutp53, whereas GOF versus non-GOF mutp53 was associated with poorer survival only among patients with LCC. This approach of collectively classifying mutp53 into GOF and non-GOF provides new insight for prognostic stratification and for understanding the mechanism of sidedness-dependent prognosis. If confirmed, future CRC clinical trials may benefit from incorporating this approach.

Biomolecules ◽  
2021 ◽  
Vol 11 (12) ◽  
pp. 1786
Aurelia Bustos ◽  
Artemio Payá ◽  
Andrés Torrubia ◽  
Rodrigo Jover ◽  
Xavier Llor ◽  

The prediction of microsatellite instability (MSI) using deep learning (DL) techniques could have significant benefits, including reducing cost and increasing MSI testing of colorectal cancer (CRC) patients. Nonetheless, batch effects or systematic biases are not well characterized in digital histology models and lead to overoptimistic estimates of model performance. Methods to not only palliate but to directly abrogate biases are needed. We present a multiple bias rejecting DL system based on adversarial networks for the prediction of MSI in CRC from tissue microarrays (TMAs), trained and validated in 1788 patients from EPICOLON and HGUA. The system consists of an end-to-end image preprocessing module that tile samples at multiple magnifications and a tissue classification module linked to the bias-rejecting MSI predictor. We detected three biases associated with the learned representations of a baseline model: the project of origin of samples, the patient’s spot and the TMA glass where each spot was placed. The system was trained to directly avoid learning the batch effects of those variables. The learned features from the bias-ablated model achieved maximum discriminative power with respect to the task and minimal statistical mean dependence with the biases. The impact of different magnifications, types of tissues and the model performance at tile vs patient level is analyzed. The AUC at tile level, and including all three selected tissues (tumor epithelium, mucin and lymphocytic regions) and 4 magnifications, was 0.87 ± 0.03 and increased to 0.9 ± 0.03 at patient level. To the best of our knowledge, this is the first work that incorporates a multiple bias ablation technique at the DL architecture in digital pathology, and the first using TMAs for the MSI prediction task.

2021 ◽  
Vol 22 (23) ◽  
pp. 12864
Chulso Moon ◽  
Maxie Gordon ◽  
David Moon ◽  
Thomas Reynolds

Microsatellite instability (MSI), the spontaneous loss or gain of nucleotides from repetitive DNA tracts, is a diagnostic phenotype for gastrointestinal, endometrial, colorectal, and bladder cancers; yet a landscape of instability events across a wider variety of cancer types is beginning to be discovered. The epigenetic inactivation of the MLH1 gene is often associated with sporadic MSI cancers. Recent next-generation sequencing (NGS)-based analyses have comprehensively characterized MSI-positive (MSI+) cancers, and several approaches to the detection of the MSI phenotype of tumors using NGS have been developed. Bladder cancer (here we refer to transitional carcinoma of the bladder) is a major cause of morbidity and mortality in the Western world. Cystoscopy, a gold standard for the detection of bladder cancer, is invasive and sometimes carries unwanted complications, while its cost is relatively high. Urine cytology is of limited value due to its low sensitivity, particularly to low-grade tumors. Therefore, over the last two decades, several new “molecular assays” for the diagnosis of urothelial cancer have been developed. Here, we provide an update on the development of a microsatellite instability assay (MSA) and the development of MSA associated with bladder cancers, focusing on findings obtained from urine analysis from bladder cancer patients as compared with individuals without bladder cancer. In our review, based on over 18 publications with approximately 900 sample cohorts, we provide the sensitivity (87% to 90%) and specificity (94% to 98%) of MSA. We also provide a comparative analysis between MSA and other assays, as well as discussing the details of four different FDA-approved assays. We conclude that MSA is a potentially powerful test for bladder cancer detection and may improve the quality of life of bladder cancer patients.

2021 ◽  
Vol 12 (1) ◽  
Olusegun Isaac Alatise ◽  
Gregory C. Knapp ◽  
Avinash Sharma ◽  
Walid K. Chatila ◽  
Olukayode A. Arowolo ◽  

AbstractUnderstanding the molecular and phenotypic profile of colorectal cancer (CRC) in West Africa is vital to addressing the regions rising burden of disease. Tissue from unselected Nigerian patients was analyzed with a multigene, next-generation sequencing assay. The rate of microsatellite instability is significantly higher among Nigerian CRC patients (28.1%) than patients from The Cancer Genome Atlas (TCGA, 14.2%) and Memorial Sloan Kettering Cancer Center (MSKCC, 8.5%, P < 0.001). In microsatellite-stable cases, tumors from Nigerian patients are less likely to have APC mutations (39.1% vs. 76.0% MSKCC P < 0.001) and WNT pathway alterations (47.8% vs. 81.9% MSKCC, P < 0.001); whereas RAS pathway alteration is more prevalent (76.1% vs. 59.6%, P = 0.03). Nigerian CRC patients are also younger and more likely to present with rectal disease (50.8% vs. 33.7% MSKCC, P < 0.001). The findings suggest a unique biology of CRC in Nigeria, which emphasizes the need for regional data to guide diagnostic and treatment approaches for patients in West Africa.

2021 ◽  
Vol 8 ◽  
Maksim Sorokin ◽  
Elizaveta Rabushko ◽  
Victor Efimov ◽  
Elena Poddubskaya ◽  
Marina Sekacheva ◽  

Microsatellite instability (MSI) is an important diagnostic and prognostic cancer biomarker. In colorectal, cervical, ovarian, and gastric cancers, it can guide the prescription of chemotherapy and immunotherapy. In laboratory diagnostics of susceptible tumors, MSI is routinely detected by the size of marker polymerase chain reaction products encompassing frequent microsatellite expansion regions. Alternatively, MSI status is screened indirectly by immunohistochemical interrogation of microsatellite binding proteins. RNA sequencing (RNAseq) profiling is an emerging source of data for a wide spectrum of cancer biomarkers. Recently, three RNAseq-based gene signatures were deduced for establishing MSI status in tumor samples. They had 25, 15, and 14 gene products with only one common gene. However, they were developed and tested on the incomplete literature of The Cancer Genome Atlas (TCGA) sampling and never validated experimentally on independent RNAseq samples. In this study, we, for the first time, systematically validated these three RNAseq MSI signatures on the literature colorectal cancer (CRC) (n = 619), endometrial carcinoma (n = 533), gastric cancer (n = 380), uterine carcinosarcoma (n = 55), and esophageal cancer (n = 83) samples and on the set of experimental CRC RNAseq samples (n = 23) for tumors with known MSI status. We found that all three signatures performed well with area under the curve (AUC) ranges of 0.94–1 for the experimental CRCs and 0.94–1 for the TCGA CRC, esophageal cancer, and uterine carcinosarcoma samples. However, for the TCGA endometrial carcinoma and gastric cancer samples, only two signatures were effective with AUC 0.91–0.97, whereas the third signature showed a significantly lower AUC of 0.69–0.88. Software for calculating these MSI signatures using RNAseq data is included.

2021 ◽  
Vol 8 (12) ◽  
pp. 1799
Momammed Mustafizur Rahman ◽  
Shabnam Imam ◽  
Sayedatun Nessa ◽  
A. K. M. Maruf Raza ◽  
Farida Arjuman ◽  

Background: This cross- sectional observational study was carried out with an aim to look for microsatellite instability (MSI) status in colorectal carcinoma and their association with different histomorphological patterns and biological behavior of colorectal carcinoma.Methods: This cross-sectional observational study was done in the Department of Pathology, Bangabandhu Sheikh Mujib Medical University Hospital (BSMMU), Dhaka, Bangladesh during September 2014 to October 2015. A total of 39 surgically resected sample of colorectal carcinoma were included. Consent from each patient was taken. The samples were histopathologically evaluated according to the standard protocol. The statistical analyses were done using Statistical packages for social sciences (SPSS 15) for Windows.Results: A total of 39 cases of colorectal carcinoma were included in this study. Majority of the patients (55.5%) was in 6th decade in MSI and 29.1% were MSI absent group. The mean age was found 47.67±10.97 years in present group and 47.84±14.26 years in absent group. The difference was not statistically significant (p>0.05). TNM stage with MSI was observed. The mean CEA level was 100.74±103.66 and 60.43±91.72. The mean Hb was 9.72±1.99 % and 9.92±2.17, the range was 7.2-12.2 and 4.6-13.4 among the groups. The mean difference was not statistically significant (p>0.05). Ulcerated was 3 (33.3%) and 19 (64.5%). Stage 3 tumor was 4 (44.4%) and 16 (51.6%). Grade 2 tumor was 5 (55.6%) and 17 (58.0%).Conclusions: For the first time in Bangladesh, this study was undertaken to evaluate the microsatellite instability (MSI) status in colorectal cancer tissue and their association with different histomorphological patterns of colorectal carcinoma.   

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