Clinical relevance of mutant-allele tumor heterogeneity and lung adenocarcinoma

Multidimensional progressive single-cell sequencing reveals cell microenvironment composition and cancer heterogeneity in lung cancer

Despite substantial advances in cancer biology and treatment, the clinical outcomes of patients with lung cancer remain unsatisfactory. The tumor microenvironment (TME) is a potential target. Using single-cell RNA sequencing, we could distinguish eight distinct cell types in the lung cancer microenvironment, demonstrating substantial intratumoral heterogeneity in 19 different lung cancer tumor samples. Through the re-dimensional grouping of cancer-associated fibroblasts (CAFs), myeloid cells, epithelial cells, natural killer (NK) cells, and T cells, the difference in the TME of lung cancer was revealed. We discovered SFTPB, SFN, and KRT8 as possible predictive biomarkers for lung cancer by assessing the gene expression patterns in epithelial cells. Examining cell-to-cell communications showed a robust association between the quantity of matrix CAFs, epithelial cells, and macrophages in the thrombospondin signaling pathway. Additionally, we found that the amyloid precursor protein signaling pathway primarily originated from the matrix, and inflammatory cancer-associated endothelial and fibroblast cells showed a co-expression relationship with myeloid cells and B cells. Through cell-to-cell correlation analysis, we found positive regulation between NK cells, regulatory T cells, GZMB-CD8 T cells, and GZMK-CD8 T cells, which could play a role in developing immune TMEs. These findings support studies on cancer heterogeneity and add to our understanding of lung cancer's cellular microenvironment.

Clinicopathologic Features and Genetic Alterations in Mixed-Type Ampullary Carcinoma

Mixed-type ampullary carcinoma is a subtype that combines intestinal-type (I-type) and pancreatobiliary-type (PB-type) lesions, but few studies have examined its clinicopathologic features and genetic alterations. The differences in genetic alterations between mixed type and other subtypes, as well as the genetic differences between I-type and PB-type lesions in the mixed type, remain unclear. In this study, we compared the clinicopathologic features and prognosis of 110 ampullary carcinomas classified by hematoxylin and eosin and immunohistochemical staining as follows: 63 PB-type, 35 I-type, and 12 mixed-type carcinomas. A comparative analysis of genetic mutations by targeted sequencing of 24 genes was also performed in 3 I-type cases, 9 PB-type cases, and I and PB-type lesions of 6 mixed-type cases. The mixed subtype had a poorer prognosis than the other subtypes, and there was also a similar tendency in the adjuvant group (n = 22). A total of 49 genetic mutations were detected in all 18 lesions for which genetic alteration was analyzed. No genetic mutations specific to the mixed type were found, and it was not possible to determine genetically whether the mixed type had originally been I or PB type. However, 5 of 6 cases had mutations common to both I and PB-type lesions, and additional mutations were found only in either I or PB-type lesions. In support of this, the mixed type more frequently exhibited genetic heterogeneity intratumorally than the other subtypes. Mixed-type tumors are histologically, immunohistochemically, and genetically heterogeneous, and this heterogeneity is associated with poor prognosis and may affect treatment resistance.

MTHFR act as a potential cancer biomarker in immune checkpoints blockades, heterogeneity, tumor microenvironment and immune infiltration

PURPOSE

To evaluate the role and landscape of 5-10-Methylenetetrahydrofolate reductase (MTHFR) to immune infiltration, tumor microenvironment, heterogeneity, immune checkpoints blockades, prognostic significance across cancer types.

METHODS

Data sets of genomic, transcriptomic and clinic features of MTHFR across > 60,000 patients and up to 44 cancer types were comprehensively analyzed using R software.

RESULTS

Expression of MTHFR gene is significantly lower in 17 tumors and correlated with overall survival (OS), disease-specific survival (DSS), progression-free interval (PFI) in specific tumors. Gene alterations of MTHFR are observed significant differences across tumor types. Expression of MTHFR is negatively correlated with the stemness index (mDNAsi, mRNAsi, DMPsi, ENHsi, EREG-mDNAsi and EREG-mRNAsi) in the most cancers. MTHFR showed significantly correlated with 67 types of immune cell infiltration scores in 44 cancer types by XCELL algorithm. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis are conducted to show the core tumor mechanism and biological process. Correlations between MTHFR and biomarkers of heterogeneity (MSI, TMB, MATH, HRD, LOH, Neoantigen, ploidy and purity) are also significant in specific tumors. MTHFR is significantly positively correlated with biomarkers of immune related genes (CD19, CD274, CD80, CD86) and mismatched repair genes (MLH1, PMS2, MSH2, MSH6, EPCAM, MLH3, PMS1, EXO1) in most cancer types. Receiver Operating Characteristics (ROC) analyses show MTHFR could act as a potential biomarker in anti-PD-1 (nivolumab to melanoma) and anti-CTLA4 (ipilimumab to melanoma) group of ontreatment, in anti-PD-1 (pembrolizumab to melanoma) group of pretreatment. Two immunohistochemistry antibodies HPA076180 and HPA077255 are verified in 20 types of tumor and could be used to detect the expression of MTHFR efficiently in clinic.

CONCLUSIONS

MTHFR could predict the response of immune checkpoints blockades, heterogeneity, tumor microenvironment and immune infiltration.

High Expression of COA6 Is Related to Unfavorable Prognosis and Enhanced Oxidative Phosphorylation in Lung Adenocarcinoma

Mitochondrial metabolism plays an important role in the occurrence and development of cancers. Cytochrome C oxidase assembly factor six (COA6) is essential in mitochondrial metabolism. However, the role of COA6 in lung adenocarcinoma (LUAD) remains unknown. Here we report that the expression of COA6 mRNA and protein were upregulated in LUAD tissues compared with lung normal tissues. We found that COA6 had high sensitivity and specificity to distinguish LUAD tissues from normal lung tissues shown by a receiver operating characteristic (ROC) curve. In addition, our univariate and multivariate Cox regression analysis indicated that COA6 was an independent unfavorable prognostic factor for LUAD patients. Furthermore, our survival analysis and nomogram showed that a high expression of COA6 mRNA was related to the short overall survival (OS) of LUAD patients. Notably, our weighted correlation network analysis (WGCNA) and functional enrichment analysis revealed that COA6 may participate in the development of LUAD by affecting mitochondrial oxidative phosphorylation (OXPHOS). Importantly, we demonstrated that depletion of COA6 could decrease the mitochondrial membrane potential (MMP), nicotinamide adenine dinucleotide (NAD) + hydrogen (H) (NADH), and adenosine triphosphate (ATP) production in LUAD cells (A549 and H1975), hence inhibiting the proliferation of these cells in vitro. Together, our study strongly suggests that COA6 is significantly associated with the prognosis and OXPHOS in LUAD. Hence, COA6 is highly likely a novel prognostic biomarker and therapeutic target of LUAD.

Predictive value of intratumor metabolic and heterogeneity parameters on [18F]FDG PET/CT for EGFR mutations in patients with lung adenocarcinoma

PURPOSE

This study aimed to investigate the value of metabolic and heterogeneity parameters of 2-deoxy-2[¹⁸F]fluoro-D-glucose ([¹⁸F]FDG) positron emission tomography/computed tomography (PET/CT) in predicting epidermal growth factor receptor (EGFR) mutations in patients with lung adenocarcinoma (ADC).

MATERIALS AND METHODS

A retrospective analysis was performed on 157 patients with lung ADC between September 2015 and June 2021, who had undergone both EGFR mutation testing and [¹⁸F]FDG PET/CT examination. Metabolic and heterogeneity parameters were measured and calculated, including maximum diameter (Dmax), maximum standardized uptake value (SUVmax), mean standardized uptake value (SUVmean), metabolic tumor volume (MTV), total lesion glycolysis (TLG), and heterogeneity factor (HF). Relationships between PET/CT parameters and EGFR mutation status were evaluated and a multivariate logistic regression analysis was analyzed to establish a combined prediction model.

RESULTS

108 (68.8%) patients exhibited EGFR mutations. EGFR mutations were more likely to occur in females (51.9% vs. 48.1%, P = 0.007), non-smokers (83.3% vs. 16.7%, P < 0.001) and right lobes (55.6% vs. 44.4%, P = 0.017). High Dmax, MTV and HF and low SUVmean were significantly correlated with EGFR mutations, and the areas under the ROC curve (AUCs) measuring 0.647, 0.701, 0.757, and 0.661, respectively. Multivariate logistic regression analysis suggested that non-smokers (OR = 0.30, P = 0.034), low SUVmean (≤ 7.75, OR = 0.63, P < 0.001) and high HF (≥ 4.21, OR = 1.80, P = 0.027) were independent predictors of EGFR mutations. The AUC of the combined prediction model measured up to 0.863, significantly higher than that of a single parameter.

CONCLUSIONS

EGFR mutant in lung ADC patients showed more intratumor heterogeneity (HF) than EGFR wild type, which was combined clinical feature (non-smokers), and metabolic parameter (SUVmean) may be helpful in predicting EGFR mutation status, thus playing a guiding role in EGFR-tyrosine kinase inhibitors (EGFR-TKIs) targeted therapies.

Plasma-Based Measurements of Tumor Heterogeneity Correlate with Clinical Outcomes in Metastatic Colorectal Cancer

Sequencing circulating tumor DNA (ctDNA) from liquid biopsies may better assess tumor heterogeneity than limited sampling of tumor tissue. Here, we explore ctDNA-based heterogeneity and its correlation with treatment outcome in STEAM, which assessed efficacy and safety of concurrent and sequential FOLFOXIRI-bevacizumab (BEV) vs. FOLFOX-BEV for first-line treatment of metastatic colorectal cancer. We sequenced 146 pre-induction and 89 post-induction patient plasmas with a 198-kilobase capture-based assay, and applied Mutant-Allele Tumor Heterogeneity (MATH), a traditionally tissue-based calculation of allele frequency distribution, on somatic mutations detected in plasma. Higher levels of MATH, particularly in the post-induction sample, were associated with shorter progression-free survival (PFS). Patients with high MATH vs. low MATH in post-induction plasma had shorter PFS (7.2 vs. 11.7 months; hazard ratio, 3.23; 95% confidence interval, 1.85−5.63; log-rank p < 0.0001). These results suggest ctDNA-based tumor heterogeneity may have potential prognostic value in metastatic cancers.

Heterogeneity among tumors with acquired resistance to EGFR tyrosine kinase inhibitors harboring EGFR ‐T790M mutation in non‐small cell lung cancer cells

EGFR‐T790M mutation is a major mechanism underlying acquired resistance to first‐ and second‐generation EGFR tyrosine kinase inhibitors (EGFR‐TKIs) in lung cancer with mutated EGFR. However, differences in the biological characteristics of T790M tumors based on treatment regimens with each generation of EGFR‐TKI are not fully understood. We established cell lines with acquired resistance harboring EGFR‐T790M mutation derived from xenograft tumors treated with each generation of EGFR‐TKI and examined their biological characteristics with respect to third‐generation EGFR‐TKI osimertinib sensitivity. Second‐generation EGFR‐TKI dacomitinib‐resistant cells with T790M‐exhibited higher sensitivity to osimertinib than first‐generation EGFR‐TKI gefitinib‐resistant cells with T790M via inhibition of AKT and ERK signaling and promotion of apoptosis. Furthermore, gefitinib‐resistant cells showed enhanced intratumor heterogeneity accompanied by genomic instability and activation of alternative resistance mechanisms compared with dacomitinib‐resistant cells; this suggests that the maintenance of EGFR dependency after acquiring resistance might depend on the type of EGFR‐TKI. Our results demonstrate that the progression of tumor heterogeneity via both genetic and non‐genetic mechanisms might affect osimertinib sensitivity in tumors with acquired resistance harboring EGFR‐T790M mutation.

Quantification of tumor heterogeneity: from data acquisition to metric generation

Tumors are unique and complex ecosystems, in which heterogeneous cell subpopulations with variable molecular profiles, aggressiveness, and proliferation potential coexist and interact. Understanding how heterogeneity influences tumor progression has important clinical implications for improving diagnosis, prognosis, and treatment response prediction. Several recent innovations in data acquisition methods and computational metrics have enabled the quantification of spatiotemporal heterogeneity across different scales of tumor organization. Here, we summarize the most promising efforts from a common experimental and computational perspective, discussing their advantages, shortcomings, and challenges. With personalized medicine entering a new era of unprecedented opportunities, our vision is that of future workflows integrating across modalities, scales, and dimensions to capture intricate aspects of the tumor ecosystem and to open new avenues for improved patient care.

Intratumor Heterogeneity as a Prognostic Factor in Solid Tumors: A Systematic Review and Meta-Analysis

Background

The landscape of intratumor heterogeneity (ITH) is present from the tumor evolution. ITH is a promising clinical indicator, but the association between ITH and prognosis remains controversial. Therefore, a meta-analysis was performed to explore whether ITH can serve as a valuable prognostic indicator in solid tumors.

Methods

All included studies were from PubMed, Embase, Cochrane, and Web of Science databases up to October 10, 2020. Studies based on ITH with available prognostic information were included. Three researchers independently completed study selection and data extraction following PRISMA guidelines. The random-effect model was used for synthesis. Hazard ratio (HR) and 95% confidence intervals (CI) were used with the endpoint defined by overall survival (OS), disease-specific survival (DFS), and progression-free survival (PFS).

Results

A total of 9,804 solid tumor patients from 21 studies were included. Analysis of specific cancers in the TCGA database showed similar results based on different ITH assessment methods, which provided the logical support for data consolidation. Available evidence revealed a negative relationship between ITH and prognosis for a specific cancer (such as lung cancer). However, the OS results from 14 tumor types showed that high ITH associated with shorter survival time [HR 1.65 (95% CI, 1.42-1.91)]. PFS and DFS analyses showed similar results [HR 1.89 (95% CI, 1.41-2.54) and HR 1.87 (95% CI, 1.15-3.04)] in general. The status of tumor metastasis and sampling models were not the confounding factors.

Conclusions

High ITH is associated with worse prognosis in many solid tumors in general although this association was absent for some cancers. ITH is expected to be a promising clinical prognostic factor for the improvement of assessment, treatment, and surveillance strategy.

Personalized drug testing in a patient with non-small-cell lung cancer using cultured cancer cells from pleural effusion

Objective

Patients with non-small-cell lung cancer (NSCLC) and primary or acquired resistance do not respond to targeted drugs. We explored whether cancer cells can be cultured from liquid biopsies from patients with primary resistance to tyrosine kinase inhibitors (TKIs). We aimed to predict patients’ responses to drugs according to in vitro drug testing results.

Methods

Cancer cell cultures were established from the pleural effusion of a patient with TKI-resistant NSCLC using a conditional reprogramming technique. Phenotypic drug sensitivity tests were performed using the Cell Counting Kit-8 assay. We tested individual drugs and compared the synergistic and inhibitory effects of drug combinations.

Results

The results of our in vitro sensitivity test using the combination of cisplatin and pemetrexed were correlated with the patient’s response.

Conclusion

This represents the first successful report of predictive testing for combination therapy in patients with epidermal growth factor receptor-mutant NSCLC and primary TKI resistance. This strategy should be applicable to both chemotherapies and targeted therapies, and it will significantly improve the clinical treatment and management of patients with NSCLC and primary or acquired resistance to targeted therapies, as well as patients lacking targetable mutations.

Clinical and immunological characteristics of sarcomas patients with clonogenic tumors

Tumorigenesis is related to the generation of heterogeneous tumor cell population, which is the result of genetic and epigenetic alterations followed by clonal selections and subsequent expansion. In basic studies genetic, histological and morphological diversity of different clones within a patient's neoplasm and specifics of their interrelation with patient's immune system are investigated mostly on the models of tumors of epithelial origin. Mesenchymal tumors such as soft tissue and bone-derived sarcomas (STBS) have been poorly studied in this regard. The molecular genetic methods used to examine intratumoral heterogeneity do not currently provide insight into which portion of the identified subclones are able to grow autonomously. Limiting dilution cloning demonstrates the existence of self-regulating tumor cells in the population and can serve as an independent prognostic predictor of poor prognosis. Intratumoral heterogeneity results not only in differences in growth dynamics, gene expression, and phenotypic markers, but also in the resistance to treatment, especially immunotherapy, thus causing tumor eluding immune escape. The changes that accompany this process can be affected by the cellular immune system, resulting in an imbalance between populations. The variations in the population composition of immune system cells are now widely debated as a predictor of response to immunotherapy, which is of obvious interest for sarcomas, where the effectiveness of chemotherapy is low and the prognosis is unfavorable, especially in case of metastatic disease development. The search for new predictive markers of disease prognosis and treatment efficacy is an important task, to which this study is focused. Our results demonstrate that clonogenic tumor characteristics such as clonogenic potential is independent predictor of unfavorable prognosis in cases of cancer and correlate with the clinical characteristics of the tumor such as overall survival (OS) and progression free survival (PFS). It was found that patients with clonogenic sarcomas had a lower content of activated cytotoxic T-lymphocytes (CTL) with the CD3⁺CD8⁺HLA^-DR⁺ phenotype and an increased number of natural NK killers (p < 0.05) compared to nonclonogenic tumors. In addition, according to our data, a high neutrophil to lymphocyte ratio (NLR), a low value of major T-lymphocyte populations, and a higher number of natural killer cells (NK) in the blood can be negative prognostic factors for the immunotherapy of this disease.

Identification of key genes and biological pathways in lung adenocarcinoma via bioinformatics analysis

Lung adenocarcinoma (LUAD) accounts for the majority of cancer-related deaths worldwide. Our study identified key LUAD genes and their potential mechanism via bioinformatics analysis of public datasets. GSE10799, GSE40791, and GSE27262 microarray datasets were retrieved from the Gene Expression Omnibus (GEO) database. The RobustRankAggreg package was used to perform a meta-analysis, and 50 upregulated genes and 87 downregulated genes overlapped in three datasets. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using the Database for Annotation, Visualization, and Integrated Discovery (DAVID). Furthermore, protein-protein interaction (PPI) networks of the differentially expressed genes (DEGs) were built by the Search Tool for the Retrieval of Interacting Genes (STRING) and 22 core genes were identified by Molecular Complex Detection (MCODE) and visualized with Cytoscape. Subsequently, these core genes were analyzed by the Kaplan-Meier Plotter and Gene Expression Profiling Interactive Analysis (GEPIA). The results showed that all 22 genes were significantly associated with reduced survival rates. For GEPIA, the expression of only one gene was not significantly different between LUAD tissues and normal tissues. A KEGG pathway enrichment reanalysis of the 21 genes identified five key genes (CCNB1, BUB1B, CDC20, TTK, and MAD2L1) in the cell cycle pathway. Finally, the Comparative Toxicogenomics Database (CTD) website was used to explore the relationship between these key genes and certain drugs. Based on the bioinformatics analysis, five key genes were identified in LUAD, and drugs closely associated these genes can provide clues for the treatment and prognosis of LUAD.

METTL7B (methyltransferase-like 7B) identification as a novel biomarker for lung adenocarcinoma

Background

Lung adenocarcinoma (LUAD) is still one of the major causes of cancer-related mortality across the globe. Therefore, there is a dire need to identify early specific and sensitive biomarkers or drug targets of LUAD for developing improved diagnosis and clinical management. We aimed to investigate the role of methyltransferase-like 7B (METTL7B) on LUAD tumor development and progression in this study.

Methods

METTL7B’s expression was confirmed in two independent clinical cohort samples, including LUAD tissues microarray (TMA) via immunohistochemistry (IHC) and serum samples via enzyme-linked immunosorbent assay (ELISA). The correlation between METTL7B expression with clinicopathological features and overall survival rate in LUAD patients was then further analyzed. Meanwhile, the messenger ribonucleic acid (mRNA) and protein levels of METTL7B were verified in cell lines and in vitro experiments, including cell proliferation assay, and migration. Invasion assays were conducted to explore the effects of METTL7B on LUAD by silencing the protein expression.

Results

METTL7B was remarkably overexpressed in clinical LUAD tumor tissues and serum compared to the normal control group and in LUAD cell lines. The expression level of METTL7B was significantly correlated with tumor size, advanced tumor node and metastases (TNM) stages, and lymph node metastasis. The Kaplan-Meier survival curves proved that high METTL7B expression was significantly associated with a reduced survival rate in LUAD patients (P<0.05), and univariate analysis showed that high METTL7B expression was significantly associated with poor overall survival [hazard ratio (HR) =2.220, 95% confidence interval (CI): 1.211–4.086; P=0.010]. In vitro assays showed that METTL7B overexpression augmented cell proliferation, migration, and the invasion in LUAD.

Conclusions

METTL7B was overexpressed in LUAD and significantly associated with the poor progression, showing that METTL7B may serve as a potential novel biomarker for the diagnosis and prognosis of LUAD. Moreover, METTL7B plays a role in promoting tumor proliferation, migration, and invasion in LUAD.

PRRX1 isoform PRRX1A regulates the stemness phenotype and epithelial-mesenchymal transition (EMT) of cancer stem-like cells (CSCs) derived from non-small cell lung cancer (NSCLC)

Backgrounds

The 2 isoforms of paired-related homeobox 1 (PRRX1), PRRX1A and PRRX1B, are critical in regulating several kinds of cancers, and figure prominently in the maintenance of stemness and progression of epithelial-mesenchymal transition (EMT). However their differential expression in non-small cell lung cancer (NSCLC) clinical samples and exact regulatory roles in cancer stem-like cells (CSCs) remain unknown.

Methods

In vitro and in vivo experiments were employed to investigate the molecular mechanism. Using CSCs, mouse models, and clinical tissues, we obtained a general picture of the relatively higher level of PRRX1A compared to PRRX1B, and PRRX1A thus promoting EMT and maintaining stemness of CSCs.

Results

PRRX1A but not PRRX1B was upregulated in lung cancer tissues and was positively correlated with TGF-β expression. In CSCs, overexpressed PRRX1A promoted malignant behaviors via transcriptional activation of TGF-β depending on TGF-β/TGF-βR signaling pathway. PRRX1A knockdown decreased self-renewal capacity accompanied by a decrease in stemness factor expression independent of the TGF-β/TGF-βR signaling pathway. Furthermore, PRRX1A was found to tightly bind to and stabilize SOX2. PRRX1A promoted sphere formation not only by enhancing stemness via stabilizing SOX2 but also by promoting cell proliferation.

Conclusions

PRRX1A, but not PRRX1B, was demonstrated to have important roles in the regulation of the stemness and metastatic potential of lung cancer, which suggests the potential application of PRRX1A in cancer treatment.

Prognostic significance of mutant-allele tumor heterogeneity in uterine corpus endometrial carcinoma

Background

Uterine corpus endometrial carcinoma (UCEC) is a clinically heterogeneous disease, and this heterogeneity is associated with tumor development, clinical characteristics, and prognostic outcomes. Mutant-allele tumor heterogeneity (MATH) is a novel, non-biased, quantitative measure to assess intra-tumor heterogeneity based on next-generation sequencing data. We aimed to explore the use of MATH as a measure for tumor heterogeneity and its prognostic role in UCEC patients.

Methods

We calculated MATH scores from the available data of 560 UCEC patients from The Cancer Genome Atlas (TCGA) and investigated their correlations with clinical characteristics, genetic alterations, and overall survival. Predictive accuracy was quantified using the area under the receiver operating characteristic curve (AUC) and the index of concordance (C-index).

Results

In total, 242 MATH scores were obtained from the UCEC cohort. MATH scores were significantly related to age, race, cancer type, clinical stage, histological grade, molecular type, targeted molecular therapy, and hormonal therapy. Furthermore, the genomic pattern on the basis of MATH scores showed that mutation rates of TP53 (tumor protein p53) and ARID1A (AT-rich interaction domain 1A) were independently associated with MATH scores. Correlation analysis revealed a significantly positive association of MATH scores with the fraction of somatic copy number alteration (SCNA). Importantly, a high MATH score was significantly associated with shorter overall survival [hazard ratio (HR), 2.342; 95% confidence interval (CI), 1.110-4.942]. Multivariate Cox regression combined with stratified analysis revealed that the MATH score is an independent prognostic factor in UCEC patients under 60 years old, and predictive quantification showed the MATH score had an AUC of 0.756 and a C-index of 0.845.

Conclusions

Our results suggest that MATH, a practical and useful way to measure intra-tumor heterogeneity, may serve as a significant biomarker for the prognosis of patients with UCEC, enabling more accurate prediction of clinical outcomes.