Defective mismatch repair associated mutational signatures, a prognostic and predictive biomarker in endometrial cancer.

5528 Background: Mismatch repair (MMR) deficiency is the distinguishing molecular feature of a significant portion of endometrial cancers (UCEC), and tumors with MMR deficiency have been identified as candidates for immune checkpoint blockade therapy. We studied MMR deficiency in UCEC using defective mismatch repair associated mutational signatures (MMRd-ams). Methods: WES-derived somatic mutation data of 531 UCEC samples from TCGA Pan-Cancer Atlas were analyzed. COSMIC mutational signatures for each sample were calculated using the R package deconstructSigs. MMRd-ams were correlated with clinical and molecular features for 507 TCGA samples (cBioPortal). Samples were divided into High MMRd-ams ( n = 192) and Low MMRd-ams ( n = 315) groups by the average of the representative MMRd-ams (0.2396). Fractions of tumor immune infiltrates were derived from CIBERSORT. Results: A significantly higher percentage of patients (47/192, 24.5%) in the High MMRd group had somatic putative driver mutations in at least 1 of the MMR genes ( MLH1, MLH3, MSH2, MSH3, MSH6, PMS1, PMS2 and EPCAM), compared with patients in the Low MMRd group (37/315, 11.8%, p = 0.0003). 15% (54/359) of tumors in the non-MSI subtypes expressed significant MMRd-ams and were categorized in the High MMRd-ams group. Patients in the High MMRd-ams group had longer progression-free survival (PFS) ( p = 0.0457, log-rank). Analysis of the inferred composition of tumor immune infiltrates revealed that the High MMRd-ams group had significantly higher fraction of CD8+ T cells ( p < 0.0001), higher fraction of T follicular helper cells ( p < 0.0001) and lower fraction of M2 macrophages ( p < 0.001). Tumors in the High MMRd-ams group also displayed higher mRNA expression levels of immune checkpoint genes: PDCD1 ( p = 0.0013), and CTLA4 ( p = 0.0016). Conclusions: MMRd-ams may be a prognostic and predictive biomarker with significant clinical impact. High MMRd-ams patients prognostically demonstrated longer PFS. Predictively, high MMRd-ams was associated with increased tumor immune infiltrates and elevated expression levels of CTLA4 and PDCD1 , known immune checkpoint genes exploitable by immune checkpoint therapies. MMRd-ams importantly characterized a subset of patients that were non-MSI but fit the MMR deficient phenotype by mutational signature. Together these findings open an avenue for recognizing and treating a previously unidentifiable group of patients.

Application of Immune Checkpoint Inhibitors in the Treatment of Cholangiocarcinoma

Cholangiocarcinoma is a general term for intrahepatic and extrahepatic malignant tumors deriving in the biliary system. According to the location, it is divided into intrahepatic cholangiocarcinoma, hilar cholangiocarcinoma, and distal cholangiocarcinoma. Progressive cholangiocarcinoma yields poor outcomes with radiotherapy; therefore, there is an urgent need for new therapeutic breakthroughs. Immune checkpoint inhibitor (ICI) therapy brings the treatment for cancer into a new field, with the use of drugs targeting PD-1/PD-L1 and CTLA-4 considerably extending the survival of patients with melanoma, lung cancer, and other solid tumors. The FDA has approved the application of pembrolizumab for solid tumors with high microsatellite instability and defective mismatch repair, including cholangiocarcinoma. Moreover, the combination of ICIs with chemotherapy and radiation therapy showed good promise. The aim of the present study was to review the application of ICIs in the treatment of cholangiocarcinoma and to summarize the reported individualized immunotherapy-based protocols and ongoing clinical trials for clinical reference.

Removal of N-Linked Glycosylation Enhances PD-L1 Detection in Colon Cancer: Validation Research Based on Immunohistochemistry Analysis

In recent years, immunotherapies have emerged as effective therapeutic strategies for treating human cancers. However, accumulating evidence has revealed an inconsistency between the response to immune checkpoint inhibitors and programmed death ligand 1 (PD-L1) expression status detected by immunohistochemistry staining. Recent research has revealed that the removal of N-Linked glycosylation significantly enhanced PD-L1 detection, resulting in both more accurate PD-L1 quantification and clinical outcome prediction. In the present study, we evaluated natural and deglycosylated PD-L1 expression in colon cancer using the PD-L1 28–8 antibody. The results of the present study validated the hypothesis that PD-L1 had a higher expression in colon cancer tissues compared with normal tissues. Additionally, colon tumors with defective mismatch repair tended to express higher PD-L1 than those without. Most importantly, the results of the present study indicated that the removal of N-linked glycosylation remarkably enhanced PD-L1 detection. Moreover, the PD-L1 signal intensity of samples with a low natural PD-L1 signal was enhanced more remarkably than that of samples with high signal intensity. Overall, our research provides an improved strategy for patient stratification for anti-PD-1/PD-L1 therapy, which deepens the clinical significance of this established strategy for treatment of colon cancer.

Computational and cellular studies reveal structural destabilization and degradation of MLH1 variants in Lynch syndrome

Defective mismatch repair leads to increased mutation rates, and germline loss-of-function variants in the repair component MLH1 cause the hereditary cancer predisposition disorder known as Lynch syndrome. Early diagnosis is important, but complicated by many variants being of unknown significance. Here we show that a majority of the disease-linked MLH1 variants we studied are present at reduced cellular levels. We show that destabilized MLH1 variants are targeted for chaperone-assisted proteasomal degradation, resulting also in degradation of co-factors PMS1 and PMS2. In silico saturation mutagenesis and computational predictions of thermodynamic stability of MLH1 missense variants revealed a correlation between structural destabilization, reduced steady-state levels and loss-of-function. Thus, we suggest that loss of stability and cellular degradation is an important mechanism underlying many MLH1 variants in Lynch syndrome. Combined with analyses of conservation, the thermodynamic stability predictions separate disease-linked from benign MLH1 variants, and therefore hold potential for Lynch syndrome diagnostics.

Ultra-Mutation in IDH Wild-Type Glioblastomas of Patients Younger than 55 Years is Associated with Defective Mismatch Repair, Microsatellite Instability, and Giant Cell Enrichment

Background: Glioblastomas (GBMs) are classified into isocitrate dehydrogenase (IDH) mutants and IDH wild-types (IDH-wt). This study aimed at identifying the mutational assets of IDH-wt GBMs in patients aged 18–54 years for which limited data are available. Methods: Sixteen IDH-wt GBMs from adults < 55 years old were explored for mutations, copy number variations, tumour mutational load (TML), and mutational spectrum by a 409 genes TML panel. Results: Eight (50%) IDH-wt GBMs were hypermutated (TML > 9 mutations/Mb) and two (12.5%) were ultra-mutated (TML > 100 mutations/Mb). One ultra-mutated GBM had microsatellite instability (MSI), a somatic MSH6 mutation, and a germline POLE mutation. The other ultra-mutated GBMs had MSI and two somatic mutations in MSH2. Both ultra-mutated GBMs featured at least 25% giant cells. The overall survival of eight patients with hypermutated GBMs was significantly longer than that of patients with non-hypermutated GBMs (p = 0.04). Conclusions: We identified a hyper-mutated subgroup among IDH-wt GBMs in adults < 55 years that had improved prognosis. Two cases were ultra-mutated and characterized by the presence of at least 25% giant cells, MMR mutations, and MSI. Since high TML has been associated with response to immune checkpoint inhibition in paediatric gliomas, the identification of a subtype of ultra-mutated IDH-wt GBM may have implications for immunotherapy.