Gene-network analysis predicts clinical response to immunotherapy in patients affected by NSCLC

OBJECTIVES

Predictive biomarkers of response to immune checkpoint inhibitors (ICIs) have been extensively studied in non-small cell lung cancer (NSCLC) with controversial results. Recently, gene-network analysis emerged as a new tool to address tumor biology and behavior, representing a potential tool to evaluate response to therapies.

METHODS

Clinical data and genetic profiles of 644 advanced NSCLCs were retrieved from cBioPortal and the Cancer Genome Atlas (TCGA); 243 ICI-treated NSCLCs were used to identify an immunotherapy response signatures via mutated gene network analysis and K-means unsupervised clustering. Signatures predictive values were tested in an external dataset of 242 cases and assessed versus a control group of 159 NSCLCs treated with standard chemotherapy.

RESULTS

At least two mutations in the coding sequence of genes belonging to the chromatin remodelling pathway (A signature), and/or at least two mutations of genes involved in cell-to-cell signalling pathways (B signature), showed positive prediction in ICI-treated advanced NSCLC. Signatures performed best when combined for patients undergoing first-line immunotherapy, and for those receiving combined ICIs.

CONCLUSIONS

Alterations in genes related to chromatin remodelling complexes and cell-to-cell crosstalk may force dysfunctional immune evasion, explaining susceptibility to immunotherapy. Therefore, exploring mutated gene networks could be valuable for determining essential biological interactions, contributing to treatment personalization.

Emergence of unique SARS-CoV-2 ORF10 variants and their impact on protein structure and function

The devastating impact of the ongoing coronavirus disease 2019 (COVID-19) on public health, caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has made targeting the COVID-19 pandemic a top priority in medical research and pharmaceutical development. Surveillance of SARS-CoV-2 mutations is essential for the comprehension of SARS-CoV-2 variant diversity and their impact on virulence and pathogenicity. The SARS-CoV-2 open reading frame 10 (ORF10) protein interacts with multiple human proteins CUL2, ELOB, ELOC, MAP7D1, PPT1, RBX1, THTPA, TIMM8B, and ZYG11B expressed in lung tissue. Mutations and co-occurring mutations in the emerging SARS-CoV-2 ORF10 variants are expected to impact the severity of the virus and its associated consequences. In this article, we highlight 128 single mutations and 35 co-occurring mutations in the unique SARS-CoV-2 ORF10 variants. The possible predicted effects of these mutations and co-occurring mutations on the secondary structure of ORF10 variants and host protein interactomes are presented. The findings highlight the possible effects of mutations and co-occurring mutations on the emerging 140 ORF10 unique variants from secondary structure and intrinsic protein disorder perspectives.

Comprehensive genomic profiling of Brazilian non-small cell lung cancer patients (GBOT 0118/LACOG0418)

Background

The aim of this study was to carry out a descriptive analysis of the somatic genetic profile and co‐occurring mutations of non‐small cell lung cancer (NSCLC) samples from patients tested with comprehensive genomic profiling (CGP).

Methods

This was a retrospective cross‐sectional study of patients diagnosed with NSCLC from 2013 to 2018 in Brazil and whose samples were submitted to CGP (FoundationOne or FoundationACT) using either tumor or circulating tumor DNA (ctDNA) from plasma.

Results

We recovered 513 CGP results from patients, 457 (89.1%) of which were from tumors and 56 (10.9%) from plasma. The median age of patients was 64 years old, of which 51.6% were males. TP53 mutations were identified in 53.6% of tumor samples, KRAS mutations in 24.2%, EGFR activating mutations were detected in 22.5%, STK11 mutations in 11.6%, PIK3CA mutations in 8.8%, ALK rearrangements in 5.4%, BRAF mutations in 5.2%, and ERBB2 alterations in 4.9%. The most commonly comutated gene was TP53. TP53 p.R337H was observed in 4.3% of samples and was associated with somatic mutations in EGFR and ERBB2 (P < 0.00001). Tumor mutational burden (TMB) analysis was available for 80.5% of samples tested, and 5.5% of samples had high TMB (≥ 20 mutations/Mb).

In conclusion, this retrospective analysis of genomic data from NSCLC patients obtained by CGP showed that common abnormalities such as EGFR mutations and ALK rearrangements had similar frequency to those previously described by other groups using others strategies. Additionally, our data confirm an association between TP53 p.R337H, supposedly germline in nature, and somatic mutations in genes of the HER family.

Key points

Significant findings of the study

This is the first report of the prevalence of driver mutations in Brazilian NSCLC patients using comprehensive genomic profiling (CGP).

The frequency of the most common driver mutations in this population was similar to that previously described in Brazil.

What this study adds

TP53 was the most commonly comutated gene across samples. TP53 p.R337H was associated with somatic mutations in EGFR and ERBB2.

Most samples had low TMB; only 5.5% of samples had high TMB.

Phylogenetic analysis and clinical characteristics of the co-occurring mutations in HA and NA genes of influenza A(H1N1)pdm09 viruses during 2015-2017 in Beijing, China

Background

Influenza A(H1N1)pdm09 viruses have undergone rapid evolution, and in recent years the complementary and antagonistic effects of HA and NA have gathered more attentions; however, the effects of co-occurring mutations in HA and NA on the patients’ clinical characteristics are still poorly understood. In this study, we analyzed molecular epidemiology and evolution of A(H1N1) pdm09, explored co-occurring mutations of HA and NA, and investigated effect of co-occurring mutations on patients’ clinical features.

Methods

A(H1N1)pdm09 was confirmed by reverse transcription-polymerase chain reaction. HA and NA genes were sequenced and phylogenetically analyzed. Clinical characteristics of the co-occurring mutations were analyzed statistically.

Results

By analyzing the HA and NA gene sequences of 33 A(H1N1)pdm09 viruses during the 2015–2017 influenza season, we found that all the viruses shared high similarities to each other and the HA genes of these viruses exclusively belonged to subclade 6B.1A. Several unreported substitutions in HA and NA proteins were observed, furthermore, co-occurring mutations of HA-V169T, A278S, E508G, D518E and NA-V67I were detected in 30.3% (10/33) A(H1N1)pdm09 virus strains when comparing with vaccine strains A/California/07/2009 and A/Michigan/45/2015 (H1N1). Sore throat was significantly associated with co-occurring mutations in HA and NA of A(H1N1)pdm09 (χ², P < 0.05).

Conclusions

Co-occurring mutations in HA and NA were detected in A(H1N1)pdm09 isolated during 2015–2017 in Beijing. Symptomatically, sore throat was associated with co-occurring mutations in HA and NA of A(H1N1)pdm09. Therefore, studying the effect and mechanism of co-occurring mutations in HA and NA on patients’ clinical features is of note needed.

Concurrent Driver Gene Mutations as Negative Predictive Factors in Epidermal Growth Factor Receptor-Positive Non-Small Cell Lung Cancer

Background

Tyrosine kinase inhibitors (TKIs) are clinically effective in non-small cell lung cancer (NSCLC) patients harbouring epidermal growth factor receptor (EGFR) oncogene mutations. Genetic factors, other than EGFR sensitive mutations, that allow prognosis of TKI treatment remain undefined.

Methods

We retrospectively screened 423 consecutive patients with advanced NSCLC and EGFR 19del or 21L858R mutations. A total of 71 patients whose progression-free survivals (PFS) were shorter than 6 months or longer than 24 months were included and stratified into separate groups. Genetic background discrepancy was analysed in the two groups using next generation sequencing (NGS).

Findings

Sensitive EGFR mutations of 19del or 21L858R were detected by NGS in all patients; the 21L858R mutation was the major type. The most frequent accompanying somatic mutations were TP53, RB1, MAP2K. ALK fusion, MET amplification, and BRAF V600E were found only in the short PFS group. Concurrent pretreament T790 M mutation was found in both groups, but was proportionally higher in the short PFS group. In the short PFS group, patients had significantly more driver gene mutations than in long PFS group (P = 0·018). The numbers of concomitant somatic mutations, EGFR pathway-related mutations, and tumor mutation burden (TMB) were not significantly different between the two groups.

Interpretation

Co-occuring driver gene mutations were negative predictive factors of TKI therapy in EGFR-mutated patients. This study highlights the importance of exploring co-occuring genomic alterations before initiation of EGFR-TKIs.