Microsatellite Instability Is Rare in the Admixed Brazilian Population of Non-Small Cell Lung Cancer: A Cohort of 526 Cases

Artificial intelligence-driven microsatellite instability profiling reveals distinctive genetic features in patients with lung cancer

BACKGROUND

Microsatellite instability (MSI) has emerged as a predictive biomarker for immunotherapy response in various cancers, but its role in non-small cell lung cancer (NSCLC) is not fully understood.

METHODS

The authors used the bioinformatics tool MIAmS to assess microsatellite status from next-generation sequencing (NGS) data using a tailored microsatellite score. Immunohistochemistry (IHC) assays were also performed to evaluate the correspondence between MSI and deficient mismatch repair (dMMR) status. A retrospective analysis of 1547 lung cancer patients was conducted, focusing on those with an MSI phenotype. Clinical characteristics, co-occurring molecular alterations, tumor mutation burden (TMB), and homologous recombination deficiency (HRD) status were evaluated in this subset.

RESULTS

Of the 1547 patients analyzed, eight (0.52%) were identified as having MSI through MIAmS, with six (0.39%) of these cases also being dMMR on IHC. All patients with dMMR had an MS score ≥2 and a history of smoking. Most patients showed loss of MLH1 and PMS2 staining on IHC. No correlation was found between MSI status and programmed death-ligand 1 expression, although all MSI patients exhibited high TMB, averaging 21.4 ± 5.6 mutations per megabase.

DISCUSSION

MSI/dMMR in lung cancer is exceedingly rare, affecting less than 1% of cases. NGS-based analysis combined with bioinformatics tools provides a robust method to identify MSI/dMMR patients, potentially guiding immunotherapy decisions. This comprehensive approach integrates molecular genotyping and MSI detection, offering personalized treatment options for lung cancer patients. NGS-based MSI testing is emerging as the preferred method for detecting microsatellite instability in various tumor types, including rare cancers.

Implementation of the ProMisE classifier and validation of its prognostic impact in Brazilian endometrial carcinomas

Purpose

Molecular classification of endometrial cancer (EC) has emerged as a key approach to individualize therapy and define prognostic outcomes. This study aimed to implement the traditional ProMisE classification in a Brazilian population, compared with a molecular setting of ProMisE biomarkers, and evaluate its impact on patients' prognosis.

Patient and methods

A prospective cohort of 114 patients with primary EC treated at Barretos Cancer Hospital (BCH) between October 2020 and December 2022 was conducted. Pathology diagnosis, staging, treatment, and follow-up data were collected. The traditional ProMisE methodology was carried out by POLE hotspot sequencing and immunohistochemistry (IHC) for p53 and mismatch repair (MMR) proteins. We further evaluate the MMR and TP53 status by molecular approach, namely microsatellite instability (MSI) by PCR-based and TP53 mutation analysis by next-generation sequencing (NGS). The results of the 4 molecular groups in both methodologies were compared regarding agreement accuracy and survival outcomes.

Results

Among the 114 cases, the traditional ProMisE groups were: POLEmut 15.8%, MMRd 28.1%, p53abn 27.2%, and no specific molecular profile (NSMP) 28.9%. Considering the molecular classification approach, we observed a POLEmut group of 15.8%, MSI group of 23.7%, TP53 mutation of 27.2%, and NSMP of 33.3%. The concordance rate of both approaches was 86.8% (99/114 cases) with an overall accuracy of 0.87. Importantly, both traditional and molecular ProMisE approaches were associated with significant distinct overall survival (OS) and progression-free survival (PFS) outcomes, with POLEmut patients exhibiting a better prognosis (93.8% OS, at 24 months), whereas the p53abn having a worse survival time (68.9% of OS, at 24 months).

Conclusion

We reported for the first time the Brazilian profile of the ProMisE classification of endometrial cancer and demonstrated the prognostic impact of the traditional and molecular ProMisE classification on patient outcomes.

Gene expression profiles (GEPs) of immuno-oncologic pathways as predictors of response to checkpoint inhibitors in advanced NSCLC

BACKGROUND

Immune checkpoint inhibitors (ICIs) revolutionized non-small-cell lung cancer (NSCLC) treatment. However, improving patients' selection for this therapy is needed. Gene expression profile (GEP) is a promising biomarker tool. We assessed the predictive value of 48 onco-immune GEPs in an NSCLC real-world scenario.

METHODS

Retrospective cohort of Brazilian NSCLC patients treated with ICIs in any line. GEP was assessed in FFPE tumor tissue using the nCounter PanCancer IO360 panel, comprising 770 cancer immune genes.

RESULTS

The median age of the 135 patients was 61 years old, most male (57.8 %), history of smoking (83.6 %), ECOG-PS 0-1 (88.7 %), clinical stage IV (91.9 %) and adenocarcinoma (65.1 %). First-line ICI in 40 % of cases, alone or in combination with chemotherapy. The median follow-up was 28 months, overall survival after starting immunotherapy (post-immunotherapy survival - PIS) was 17.8 months, and real-world progression-free survival was 5.5 months. The GEP analysis was possible in 66 patients. We found that 14 different GEPs associated with PIS, namely IDO1, PD-L2, Cytotoxicity, Cytotoxic Cells, IFN Downstream, CTLA4, PD-L1, TIGIT, Lymphoid, Immunoproteasome, Exhausted CD8, IFN Gamma, TIS and APM. TIS and IFN-γ were the most significant GEPs associated with favorable outcomes. The median PIS for patients with high TIS expression was 29.2 versus 15.5 months (HR 0.42; 95 %CI; 0.17-0.67; p<0.05) for those with low expression. Similar results were observed for IFN-γ.

CONCLUSIONS

The TIS (tumor inflammation signature) and IFN-γ signatures constitute predictive biomarkers to identify patients with NSCLC patients who would possibly benefit from ICI therapies.

Correlation of Programmed Death-Ligand 1 Expression With Lung Adenocarcinoma Histologic and Molecular Subgroups in Primary and Metastatic Sites

Programmed death-ligand 1 (PD-L1) expression in terms of the tumor proportion score (TPS) is the main predictive biomarker approved for immunotherapy against lung nonsmall cell carcinoma. Although some studies have explored the associations between histology and PD-L1 expression in pulmonary adenocarcinoma, they have been limited in sample size and/or extent of examined histologic variables, which may have resulted in conflicting information. In this observational retrospective study, we identified primary and metastatic lung adenocarcinoma cases in the span of 5 years and tabulated the detailed histopathologic features, including pathological stage, tumor growth pattern, tumor grade, lymphovascular and pleural invasion, molecular alterations, and the associated PD-L1 expression for each case. Statistical analyses were performed to detect associations between PD-L1 and these features. Among 1658 cases, 643 were primary tumor resections, 751 were primary tumor biopsies, and 264 were metastatic site biopsies or resections. Higher TPS significantly correlated with high-grade growth patterns, grade 3 tumors, higher T and N stage, presence of lymphovascular invasion, and presence of MET and TP53 alterations, whereas lower TPS correlated with lower-grade tumors and presence of EGFR alterations. There was no difference in PD-L1 expression in matched primary and metastases, although higher TPS was observed in metastatic tumors due to the presence of high-grade patterns in these specimens. TPS showed a strong association with a histologic pattern. Higher-grade tumors had higher TPS, which is also associated with more aggressive histologic features. Tumor grade should be kept in mind when selecting cases and blocks for PD-L1 testing.

Biomarkers for Immune Checkpoint Inhibitor Response in NSCLC: Current Developments and Applicability

Lung cancer has the highest mortality rate among all cancer types, resulting in over 1.8 million deaths annually. Immunotherapy utilizing immune checkpoint inhibitors (ICIs) has revolutionized the treatment of non-small cell lung cancer (NSCLC). ICIs, predominantly monoclonal antibodies, modulate co-stimulatory and co-inhibitory signals crucial for maintaining immune tolerance. Despite significant therapeutic advancements in NSCLC, patients still face challenges such as disease progression, recurrence, and high mortality rates. Therefore, there is a need for predictive biomarkers that can guide lung cancer treatment strategies. Currently, programmed death-ligand 1 (PD-L1) expression is the only established biomarker for predicting ICI response. However, its accuracy and robustness are not consistently reliable. This review provides an overview of potential biomarkers currently under development or in the validation stage that hold promise in improving the classification of responders and non-responders to ICI therapy in the near future.

Long-term benefit of immunotherapy in a patient with squamous lung cancer exhibiting mismatch repair deficient/high microsatellite instability/high tumor mutational burden: A case report and literature review

Genetic mutations that render mismatch repair defective may result in microsatellite instability, which is common in colorectal carcinomas and gastric cancers as well as Lynch syndrome. Mismatch repair deficiency/high microsatellite instability (dMMR/MSI-H) predicts the tumor response to immune checkpoint inhibitors. However, few studies have evaluated the efficacy of immune checkpoint inhibitors in non-small cell lung cancer (NSCLC) patients with dMMR/MSI-H. In this work, we present a patient with advanced squamous lung cancer with dMMR/MSI-H and a high tumor mutational burden (TMB-H) who obtained a long-term benefit from immunotherapy. NSCLC patients with dMMR/MSI-H/TMB-H may thus benefit from immune checkpoint inhibitors.

Case report: anaplastic lymphoma kinase (ALK) rearranged adenocarcinoma with high level of microsatellite instability response to pembrolizumab

The presence of anaplastic lymphoma kinase (ALK) rearrangement is reported to be related to the lack of efficacy of immune checkpoint inhibitors (ICIs). High levels of microsatellite instability (MSI-high) are important biomarkers of ICIs, particularly in colorectal cancer. The therapeutic effect of ICIs for MSI-high NSCLC is uncertain because of the rarity of these tumors. Here we report a case of ALK rearranged NSCLC with MSI-high. A 48-year-old male was diagnosed with lung adenocarcinoma, cT4N3M1a, stage IVA with ALK rearrangement, high PD-L1 expression with a tumor proportion score (TPS) of 100%, and MSI-high. The patient was treated with alectinib as the first-line therapy but progressed at five months with left atrial invasion re-expansion. The patient discontinued alectinib and was switched to pembrolizumab monotherapy. After two months, left atrial invasion significantly decreased. The patient continued pembrolizumab for a year without noticeable adverse events, and tumor shrinkage persisted. This case supports the efficacy of ICIs for MSI-high NSCLC, even in the presence of ALK rearrangement.

Microsatellite instability-related prognostic risk score (MSI-pRS) defines a subset of lung squamous cell carcinoma (LUSC) patients with genomic instability and poor clinical outcome

Background: Lung squamous cell carcinoma (LUSC) shares less typical onco-drivers and target resistance, but a high overall mutation rate and marked genomic complexity. Mismatch repair (MMR) deficiency leads to microsatellite instability (MSI) and genomic instability. MSI is not an ideal option for prognosis of LUSC, whereas its function deserves exploration. Method: MSI status was classified by MMR proteins using unsupervised clustering in the TCGA-LUSC dataset. The MSI score of each sample was determined by gene set variation analysis. Intersections of the differential expression genes and differential methylation probes were classified into functional modules by weighted gene co-expression network analysis. Least absolute shrinkage and selection operator regression and stepwise gene selection were performed for model downscaling. Results: Compared with the MSI-low (MSI-L) phenotype, MSI-high (MSI-H) displayed higher genomic instability. The MSI score was decreased from MSI-H to normal samples (MSI-H > MSI-L > normal). A total of 843 genes activated by hypomethylation and 430 genes silenced by hypermethylation in MSI-H tumors were classified into six functional modules. CCDC68, LYSMD1, RPS7, and CDK20 were used to construct MSI-related prognostic risk score (MSI-pRS). Low MSI-pRS was a protective prognostic factor in all cohorts (HR = 0.46, 0.47, 0.37; p-value = 7.57e-06, 0.009, 0.021). The model contains tumor stage, age, and MSI-pRS that showed good discrimination and calibration. Decision curve analyses indicated that microsatellite instability-related prognostic risk score added extra value to the prognosis. A low MSI-pRS was negatively correlated with genomic instability. LUSC with low MSI-pRS was associated with increased genomic instability and cold immunophenotype. Conclusion: MSI-pRS is a promising prognostic biomarker in LUSC as the substitute of MSI. Moreover, we first declared that LYSMD1 contributed to genomic instability of LUSC. Our findings provided new insights in the biomarker finder of LUSC.

A Screening of Epigenetic Therapeutic Targets for Non-Small Cell Lung Cancer Reveals PADI4 and KDM6B as Promising Candidates

Despite advances in diagnostic and therapeutic approaches for lung cancer, new therapies targeting metastasis by the specific regulation of cancer genes are needed. In this study, we screened a small library of epigenetic inhibitors in non-small-cell lung cancer (NSCLC) cell lines and evaluated 38 epigenetic targets for their potential role in metastatic NSCLC. The potential candidates were ranked by a streamlined approach using in silico and in vitro experiments based on publicly available databases and evaluated by real-time qPCR target gene expression, cell viability and invasion assays, and transcriptomic analysis. The survival rate of patients with lung adenocarcinoma is inversely correlated with the gene expression of eight epigenetic targets, and a systematic review of the literature confirmed that four of them have already been identified as targets for the treatment of NSCLC. Using nontoxic doses of the remaining inhibitors, KDM6B and PADI4 were identified as potential targets affecting the invasion and migration of metastatic lung cancer cell lines. Transcriptomic analysis of KDM6B and PADI4 treated cells showed altered expression of important genes related to the metastatic process. In conclusion, we showed that KDM6B and PADI4 are promising targets for inhibiting the metastasis of lung adenocarcinoma cancer cells.

Clinical utility of liquid biopsy-based companion diagnostics in the non-small-cell lung cancer treatment

Recently, technological advances in the detection and biological characterization of circulating tumor DNA (ctDNA) have enabled the implementation of liquid biopsy testing into clinical practice. Methods for analysis of liquid biopsies have rapidly evolved over the past few years and have continued to advance, thus providing details about tumor biological characteristics such as tumor progression, metastasis, tumor heterogeneity, genomic mutation profile, clonal evolution, etc. In tandem with technological advances, the implementation of liquid biopsy in routine clinical settings has proceeded. In 2016, the Food and Drug Administration (FDA) approved the first ctDNA liquid biopsy test to detect epidermal growth factor receptor (EGFR) gene mutations in patients with non-small-cell lung cancer (NSCLC) as a companion diagnostic for molecular targeted drug of EGFR-tyrosine kinase inhibitor (TKI, EGFR-TKI). More recently, multigene panel assays of liquid biopsy have been approved as companion diagnostics and have been used in routine clinical settings. The estimation of blood tumor mutation burden (bTMB) to predict the efficacy of immune checkpoint inhibitor (ICI) treatment can be one of the promising approaches to liquid biopsy. The next stage of implementation of liquid biopsy for routine clinical settings is for monitoring of ctDNA after surgical treatment to predict prognosis and to detect disease relapse earlier than conventional imaging diagnosis. Its clinical utility is under assessment in several clinical trials. This review introduces recent advances in liquid biopsy methodology, the development of biomarkers, and its clinical utility in the treatment of NSCLC patients.