Machine learning developed an intratumor heterogeneity signature for predicting prognosis and immunotherapy benefits in cholangiocarcinoma

BACKGROUND

Cholangiocarcinoma is a kind of epithelial cell malignancy with high mortality. Intratumor heterogeneity (ITH) is involved in tumor progression, aggressiveness, treatment resistance, and disease recurrence.

METHODS

Integrative machine learning procedure including 10 methods (random survival forest, elastic network, Lasso, Ridge, stepwise Cox, CoxBoost, partial least squares regression for Cox, supervised principal components, generalized boosted regression modeling, and survival support vector machine) was performed to construct an ITH-related signature (IRS) for cholangiocarcinoma. Single cell analysis was performed to clarify the communication between immune cell subtypes. Cellular experiment was used to verify the biological function of hub gene.

RESULTS

The optimal prognostic IRS developed by Lasso method served as an independent risk factor and had a stable and powerful performance in predicting the overall survival rate in cholangiocarcinoma, with the AUC of 2-, 3-, and 4-year ROC curve being 0.955, 0.950 and 1.000 in TCGA cohort. low IRS score indicated with a lower tumor immune dysfunction and exclusion score, lower tumor microsatellite instability, lower immune escape score, lower MATH score, and higher mutation burden score in cholangiocarcinoma. Single cell analysis revealed a strong communication between fibroblasts, microphage and epithelial cells by specific ligand-receptor pairs, including COL4A1-(ITGAV+ITGB8) and COL1A2-(ITGAV+ITGB8). Down-regulation of BET1L inhibited the proliferation, migration and invasion as well as promoted apoptosis of cholangiocarcinoma cell.

CONCLUSION

Integrative machine learning analysis was performed to construct a novel IRS in cholangiocarcinoma. This IRS acted as an indicator for predicting the prognosis and immunotherapy benefits of cholangiocarcinoma patients.

Up-regulation of RAN by MYBL2 maintains osteosarcoma cancer stem-like cells population during heterogeneous tumor generation

Intratumor heterogeneity is one of the major features of cancers, leading to aggressive disease and treatment failure. Cancer stem-like cells (CSCs) are believed to give rise to the heterogeneous cell types within tumors. Hence, understanding the regulatory mechanism underlying the recurrence process of heterogeneous tumor by CSCs could facilitate the development of CSC-targeted therapies. Here, utilizing single-cell transcriptomics, we present the molecular profile of osteosarcoma CSCs-derived heterogeneous tumors consisting of CSC clusters, osteoprogenitor and differentiated cell types, such as pre-osteoblasts, osteoblasts and chondroblasts. Furthermore, by constructing the comprehensive map of modulated genes during CSCs self-renewal and differentiation, we identify RAN exhibiting specific peak expression in osteosarcoma CSCs clusters which is transcriptionally up-regulated by MYBL2. Functionality, MYBL2-RAN pathway promotes the CSCs self-renewal by enhancing the nuclear accumulation of MYC protein, which in turn boosts the overexpression of RAN as a positive feedback. Importantly, blockage of MYBL2-RAN pathway sensitizes CSCs to cisplatin treatment and synergistically enhanced the cisplatin-induced cytotoxicity. Both MYBL2 and RAN are highly expressed in clinical osteosarcoma tissues which indicate poor prognosis. Collectively, our study provides advanced insights into the regeneration process of heterogeneous tumor originating from CSCs and highlights the MYBL2-RAN pathway as a promising target for CSC-based therapy in osteosarcoma.

Advanced insights on tumor-associated macrophages revealed by single-cell RNA sequencing: The intratumor heterogeneity, functional phenotypes, and cellular interactions

Single-cell RNA sequencing (scRNA-seq) is an emerging technology used for cellular transcriptome analysis. The application of scRNA-seq has led to profoundly advanced oncology research, continuously optimizing novel therapeutic strategies. Intratumor heterogeneity extensively consists of all tumor components, contributing to different tumor behaviors and treatment responses. Tumor-associated macrophages (TAMs), the core immune cells linking innate and adaptive immunity, play significant roles in tumor progression and resistance to therapies. Moreover, dynamic changes occur in TAM phenotypes and functions subject to the regulation of the tumor microenvironment. The heterogeneity of TAMs corresponding to the state of the tumor microenvironment has been comprehensively recognized using scRNA-seq. Herein, we reviewed recent research and summarized variations in TAM phenotypes and functions from a developmental perspective to better understand the significance of TAMs in the tumor microenvironment.

Single-cell RNA sequencing of anaplastic ependymoma and H3K27M-mutant diffuse midline glioma

BACKGROUND

Anaplastic ependymoma and H3K27M-mutant diffuse midline glioma are two common subtypes of brain tumors with poor long-term prognosis. The present study analyzed and compared the differences in cell types between two tumors by single-cell RNA sequencing (scRNA-seq) technology.

METHODS

ScRNA-seq was performed to profile cells from cancer tissue from anaplastic ependymoma patient and H3K27M-mutant diffuse midline glioma patient. Cell clustering, marker gene identification, cell type annotation, copy number variation analysis and function analysis of differentially expressed genes were then performed.

RESULTS

A total of 11,219 cells were obtained from anaplastic ependymoma and H3K27M mutant diffuse midline glioma, and these cells categorized into 12 distinct clusters. Each cell cluster could be characterized with specific cell markers to indicate cellular heterogeneity. Five cell types were annotated in each sample, including astrocyte, oligodendrocytes, microglial cell, neural progenitor cell and immune cell. The cluster types and proportion of cell types were not consistent between the two brain tumors. Functional analyses suggest that these cell clusters are involved in tumor-associated pathways, with slight differences in the cells of origin between the two tumors. In addition, cell communication analysis showed that the NRG3-ERBB4 pair is a key Ligand-receptor pair for anaplastic ependymoma, while in H3K27M-mutant diffuse midline glioma it is the PTN-PTPRZ1 pair that establishes contact with other cells.

CONCLUSION

There was intratumor heterogeneity in anaplastic ependymoma and H3K27M mutant diffuse midline glioma, and that the subtype differences may be due to differences in the origin of the cells.

Mapping three-dimensional intratumor proteomic heterogeneity in uterine serous carcinoma by multiregion microsampling

BACKGROUND

Although uterine serous carcinoma (USC) represents a small proportion of all uterine cancer cases, patients with this aggressive subtype typically have high rates of chemotherapy resistance and disease recurrence that collectively result in a disproportionately high death rate. The goal of this study was to provide a deeper view of the tumor microenvironment of this poorly characterized uterine cancer variant through multi-region microsampling and quantitative proteomics.

METHODS

Tumor epithelium, tumor-involved stroma, and whole "bulk" tissue were harvested by laser microdissection (LMD) from spatially resolved levels from nine USC patient tumor specimens and underwent proteomic analysis by mass spectrometry and reverse phase protein arrays, as well as transcriptomic analysis by RNA-sequencing for one patient's tumor.

RESULTS

LMD enriched cell subpopulations demonstrated varying degrees of relatedness, indicating substantial intratumor heterogeneity emphasizing the necessity for enrichment of cellular subpopulations prior to molecular analysis. Known prognostic biomarkers were quantified with stable levels in both LMD enriched tumor and stroma, which were shown to be highly variable in bulk tissue. These USC data were further used in a comparative analysis with a data generated from another serous gynecologic malignancy, high grade serous ovarian carcinoma, and have been added to our publicly available data analysis tool, the Heterogeneity Analysis Portal ( https://lmdomics.org/ ).

CONCLUSIONS

Here we identified extensive three-dimensional heterogeneity within the USC tumor microenvironment, with disease-relevant biomarkers present in both the tumor and the stroma. These data underscore the critical need for upfront enrichment of cellular subpopulations from tissue specimens for spatial proteogenomic analysis.

ATACAmp: a tool for detecting ecDNA/HSRs from bulk and single-cell ATAC-seq data

BACKGROUND

High oncogene expression in cancer cells is a major cause of rapid tumor progression and drug resistance. Recent cancer genome research has shown that oncogenes as well as regulatory elements can be amplified in the form of extrachromosomal DNA (ecDNA) or subsequently integrated into chromosomes as homogeneously staining regions (HSRs). These genome-level variants lead to the overexpression of the corresponding oncogenes, resulting in poor prognosis. Most existing detection methods identify ecDNA using whole genome sequencing (WGS) data. However, these techniques usually detect many false positive regions owing to chromosomal DNA interference.

RESULTS

In the present study, an algorithm called "ATACAmp" that can identify ecDNA/HSRs in tumor genomes using ATAC-seq data has been described. High chromatin accessibility, one of the characteristics of ecDNA, makes ATAC-seq naturally enriched in ecDNA and reduces chromosomal DNA interference. The algorithm was validated using ATAC-seq data from cell lines that have been experimentally determined to contain ecDNA regions. ATACAmp accurately identified the majority of validated ecDNA regions. AmpliconArchitect, the widely used ecDNA detecting tool, was used to detect ecDNA regions based on the WGS data of the same cell lines. Additionally, the Circle-finder software, another tool that utilizes ATAC-seq data, was assessed. The results showed that ATACAmp exhibited higher accuracy than AmpliconArchitect and Circle-finder. Moreover, ATACAmp supported the analysis of single-cell ATAC-seq data, which linked ecDNA to specific cells.

CONCLUSIONS

ATACAmp, written in Python, is freely available on GitHub under the MIT license: https://github.com/chsmiss/ATAC-amp . Using ATAC-seq data, ATACAmp offers a novel analytical approach that is distinct from the conventional use of WGS data. Thus, this method has the potential to reduce the cost and technical complexity associated ecDNA analysis.

Characterization of tumour microenvironment reprogramming reveals invasion in epithelial ovarian carcinoma

BACKGROUND

Patients with epithelial ovarian carcinoma (EOC) are usually diagnosed at an advanced stage with tumour cell invasion. However, identifying the underlying molecular mechanisms and biomarkers of EOC proliferation and invasion remains challenging.

RESULTS

Herein, we explored the relationship between tumour microenvironment (TME) reprogramming and tissue invasion based on single-cell RNA sequencing (scRNA-seq) datasets. Interestingly, hypoxia, oxidative phosphorylation (OXPHOS) and glycolysis, which have biologically active trajectories during epithelial mesenchymal transition (EMT), were positively correlated. Moreover, energy metabolism and anti-apoptotic activity were found to be critical contributors to intratumor heterogeneity. In addition, HMGA1, EGR1 and RUNX1 were found to be critical drivers of the EMT process in EOC. Experimental validation revealed that suppressing EGR1 expression inhibited tumour cell invasion, significantly upregulated the expression of E-cadherin and decreased the expression of N-cadherin. In cell components analysis, cancer-associated fibroblasts (CAFs) were found to significantly contribute to immune infiltration and tumour invasion, and the accumulation of CAFs was associated with poorer patient survival.

CONCLUSION

We revealed the molecular mechanism and biomarkers of tumour invasion and TME reprogramming in EOC, which provides effective targets for the suppression of tumour invasion.

Phenotypically sorted highly and weakly migratory triple negative breast cancer cells exhibit migratory and metastatic commensalism

BACKGROUND

Intratumor heterogeneity is a well-established hallmark of cancer that impedes cancer research, diagnosis, and treatment. Previously, we phenotypically sorted human breast cancer cells based on migratory potential. When injected into mice, highly migratory cells were weakly metastatic and weakly migratory cells were highly metastatic. The purpose of this study was to determine whether these weakly and highly migratory cells interact with each other in vitro or in vivo.

METHODS

To assess the relationship between heterogeneity in cancer cell migration and metastatic fitness, MDA-MB-231 and SUM159PT triple negative breast cancer cells were phenotypically sorted into highly migratory and weakly migratory subpopulations and assayed separately and in a 1:1 mixture in vitro and in vivo for metastatic behaviors. Unpaired, two-tailed Student's t-tests, Mann-Whitney tests, ordinary, one-way ANOVAs, and Kruskal-Wallis H tests were performed as appropriate with p < 0.05 as the cutoff for statistical significance.

RESULTS

When highly and weakly migratory cells are co-seeded in mixed spheroids, the weakly migratory cells migrated farther than weakly migratory only spheroids. In mixed spheroids, leader-follower behavior occurred with highly migratory cells leading the weakly migratory cells in migration strands. When cell suspensions of highly migratory, weakly migratory, or a 1:1 mixture of both subpopulations were injected orthotopically into mice, both the mixed cell suspensions and weakly migratory cells showed significant distal metastasis, but the highly migratory cells did not metastasize significantly to any location. Notably, significantly more distal metastasis was observed in mice injected with the 1:1 mixture compared to either subpopulation alone.

CONCLUSIONS

This study suggests that weakly migratory cells interact with highly migratory cells in a commensal fashion resulting in increased migration and metastasis. Together, these findings indicate that cancer cell subpopulation migration ability does not correlate with metastatic potential and that cooperation between highly migratory and weakly migratory subpopulations can enhance overall metastatic fitness.

The tumour ecology of quiescence: Niches across scales of complexity

Quiescence is a state of cell cycle arrest, allowing cancer cells to evade anti-proliferative cancer therapies. Quiescent cancer stem cells are thought to be responsible for treatment resistance in glioblastoma, an aggressive brain cancer with poor patient outcomes. However, the regulation of quiescence in glioblastoma cells involves a myriad of intrinsic and extrinsic mechanisms that are not fully understood. In this review, we synthesise the literature on quiescence regulatory mechanisms in the context of glioblastoma and propose an ecological perspective to stemness-like phenotypes anchored to the contemporary concepts of niche theory. From this perspective, the cell cycle regulation is multiscale and multidimensional, where the niche dimensions extend to extrinsic variables in the tumour microenvironment that shape cell fate. Within this conceptual framework and powered by ecological niche modelling, the discovery of microenvironmental variables related to hypoxia and mechanosignalling that modulate proliferative plasticity and intratumor immune activity may open new avenues for therapeutic targeting of emerging biological vulnerabilities in glioblastoma.

Effects of Heterogeneity on Cancer: A Game Theory Perspective

In this study, we explore interactions between cancer cells by using the hawk-dove game. We analyze the heterogeneity of tumors by considering games with populations composed of 2 or 3 types of cell. We determine what strategies are evolutionarily stable in the 2-type and 3-type population games and what the corresponding expected payoffs are. Our results show that the payoff of the best-off cell in the 2-type population game is higher than that of the best-off cell in the 3-type population game. When these mathematical findings are transferred to the field of oncology they suggest that a tumor with low intratumor heterogeneity pursues a more aggressive course than one with high intratumor heterogeneity. Some histological and genomic data on clear cell renal cell carcinomas is consistent with these results. We underline the importance of identifying intratumor heterogeneity in routine practice and suggest that therapeutic strategies that preserve heterogeneity may be promising as they may slow down cancer growth.

Quantification of subtype purity in Luminal A breast cancer predicts clinical characteristics and survival

PURPOSE

PAM50 profiling assigns each breast cancer to a single intrinsic subtype based on a bulk tissue sample. However, individual cancers may show evidence of admixture with an alternate subtype that could affect prognosis and treatment response. We developed a method to model subtype admixture using whole transcriptome data and associated it with tumor, molecular, and survival characteristics for Luminal A (LumA) samples.

METHODS

We combined TCGA and METABRIC cohorts and obtained transcriptome, molecular, and clinical data, which yielded 11,379 gene transcripts in common and 1,178 cases assigned to LumA. We used semi-supervised non-negative matrix factorization (ssNMF) to compute the subtype admixture proportions of the four major subtypes-pLumA, pLumB, pHER2, and pBasal-for each case and measured associations with tumor characteristics, molecular features, and survival.

RESULTS

Luminal A cases in the lowest versus highest quartile for pLumA transcriptomic proportion had a 27% higher prevalence of stage > 1, nearly a threefold higher prevalence of TP53 mutation, and a hazard ratio of 2.08 for overall mortality. We found positive associations between pHER2 and HER2 positivity by IHC or FISH; between pLumB and PR negativity; and between pBasal and younger age, node positivity, TP53 mutation, and EGFR expression. Predominant basal admixture, in contrast to predominant LumB or HER2 admixture, was not associated with shorter survival.

CONCLUSION

Bulk sampling for genomic analyses provides an opportunity to expose intratumor heterogeneity, as reflected by subtype admixture. Our results elucidate the striking extent of diversity among LumA cancers and suggest that determining the extent and type of admixture holds promise for refining individualized therapy. LumA cancers with a high degree of basal admixture appear to have distinct biological characteristics that warrant further study.

Single-nucleus and Spatially Resolved Intratumor Subtype Heterogeneity in Bladder Cancer

Background

Current bulk transcriptomic classification systems for bladder cancer do not consider the level of intratumor subtype heterogeneity.

Objective

To investigate the extent and possible clinical impact of intratumor subtype heterogeneity across early and more advanced stages of bladder cancer.

Design setting and participants

We performed single-nucleus RNA sequencing (RNA-seq) of 48 bladder tumors and additional spatial transcriptomics for four of these tumors. Total bulk RNA-seq and spatial proteomics data were available from the same tumors for comparison, along with detailed clinical follow-up of the patients.

Outcome measurements and statistical analysis

The primary outcome was progression-free survival for non-muscle-invasive bladder cancer. Cox regression analysis, log-rank tests, Wilcoxon rank-sum tests, Spearman correlation, and Pearson correlation were used for statistical analysis.

Results and limitations

We found that the tumors exhibited varying levels of intratumor subtype heterogeneity and that the level of subtype heterogeneity can be estimated from both single-nucleus and bulk RNA-seq data, with high concordance between the two. We found that a higher class 2a weight estimated from bulk RNA-seq data is associated with worse outcome for patients with molecular high-risk class 2a tumors. The sparsity of the data generated using the DroNc-seq sequencing protocol is a limitation.

Conclusions

Our results indicate that discrete subtype assignments from bulk RNA-seq data may lack biological granularity and that continuous class scores may improve clinical risk stratification of patients with bladder cancer.

Patient summary

We found that several molecular subtypes can exist within a single bladder tumor and that continuous subtype scores can be used to identify a subgroup of patients with poor outcomes. Use of these subtype scores may improve risk stratification for patients with bladder cancer, which can help in making decisions on treatment.

bITH, a blood-based metric of intratumor heterogeneity, is associated with clinical response to immune checkpoint blockade in non-small cell lung cancer

BACKGROUND

Intratumor heterogeneity (ITH) has been associated with poor prognosis in advanced non-small cell cancer (NSCLC) patients receiving immune checkpoint blockade (ICB) therapies. However, there is currently no evidence supporting an ITH metric as a predictor of clinical benefit from ICB. The unique advantages of blood make it a promising material for ITH estimation and relevant applications. This study aims to develop and validate a blood-based ITH index for predicting ICB response.

METHODS

NSCLC patients from the OAK and POPLAR clinical trials were used as the training cohorts for algorithm development. Survival analyses with overall survival (OS) and progression-free survival (PFS) as endpoints were performed to assess clinical response. The predictive value of bITH was subsequently validated with an independent cohort of 42 NSCLC patients treated with PD-1 blockade.

FINDINGS

bITH was significantly associated with the differential OS and PFS elicited by atezolizumab vs. docetaxel in both univariable and multivariable analyses in the OAK patients, suggesting bITH as an independent predictor for response to ICB. Moreover, compared with blood tumor mutation burden (bTMB), bITH enabled greater OS segregation and comparable PFS segregation, and obtained a predictive role regardless of bTMB status. Moreover, the association between bITH and PFS was validated with an independent cohort.

INTERPRETATION

Patients with low blood-based ITH metric manifest significant OS and PFS benefit from immunotherapy versus chemotherapy. Future research is awaited to corroborate our findings and to enrich the clinical utility of ITH.

FUNDING

This study was supported by the National Natural Science Foundation of China (Nos. 81972718 and 81572321), the Natural Scientific Foundation of Zhejiang Province, China (No. LY19H160007), the Science and Technology Program for Health and Medicine in Zhejiang Province, China (No. 2021KY541), the Scientific Research Project, Science and Technology Department of Sichuan Province (No. 21YYJC1616), the Scientific Research Project, Sichuan Medical Association (No. S20002), Wu Jieping Medical Foundation (No. 320.6750), and 2018 Entrepreneurial Leading Talent of Guangzhou Huangpu District and Guangzhou Development District (No. 2022-L023).

Defining multiple layers of intratumor heterogeneity based on variations of perturbations in multi-omics profiling

BACKGROUND

Intratumor heterogeneity (ITH) plays a crucial role in tumor progression, relapse, immune evasion, and drug resistance. Existing ITH quantification methods based on a single molecular level are inadequate to capture ITH evolving from genotype to phenotype.

METHODS

We designed a set of information entropy (IE)-based algorithms for quantifying ITH at the genome (somatic copy number alterations and mutations), mRNA, microRNA (miRNA), long non-coding RNA (lncRNA), protein, and epigenome level, respectively. We evaluated the performance of these algorithms by analyzing the correlations between their ITH scores and ITH-associated molecular and clinical features in 33 TCGA cancer types. Moreover, we evaluated the correlations between the ITH measures at different molecular levels by Spearman correlation and clustering analysis.

RESULTS

The IE-based ITH measures had significant correlations with unfavorable prognosis, tumor progression, genomic instability, antitumor immunosuppression, and drug resistance. The mRNA ITH showed stronger correlations with the miRNA, lncRNA, and epigenome ITH than with the genome ITH, supporting the regulatory relationships of miRNA, lncRNA, and DNA methylation towards mRNA. The protein-level ITH displayed stronger correlations with the transcriptome-level ITH than with the genome-level ITH, supporting the central dogma of molecular biology. Clustering analysis based on the ITH scores identified four subtypes of pan-cancer showing significantly different prognosis. Finally, the ITH integrating the seven ITH measures displayed more prominent properties of ITH than that at a single level.

CONCLUSIONS

This analysis provides landscapes of ITH at various molecular levels. Combining the ITH observation from different molecule levels will improve personalized management for cancer patients.

Intratumor heterogeneity is associated with less CD8+ T cell infiltration and worse survival in patients with small cell lung cancer

PURPOSE

Small cell lung cancer (SCLC) is a heterogeneous malignancy with genetic and phenotypic disparity. However, the association between intratumor heterogeneity (ITH) and immunological features as well as the impact of ITH on prognosis has never been explored in SCLC. Hence, we investigated the relationship between ITH and their immunological features and explored the effect of ITH on overall survival (OS) in patients with SCLC.

METHODS

Programmed cell death-ligand 1 (PD-L1), CD8⁺ cell infiltration was calculated through immunohistochemical staining and tumor mutational burden (TMB), tumor neoantigen burden (TNB), and ITH levels via whole-exome sequencing (WES).

RESULTS

Significant correlation was not found in ITH versus TMB, ITH versus TNB (P = 0.1821, P = 0.0612). No significant variation in ITH was found between negative PD-L1 SCLC patients and positive PD-L1 ones (P = 0.0610 for TPS, P = 0.6347 for CPS). Interestingly, we demonstrated the negative correlation between CD8⁺ T cell infiltration and ITH (P = 0.0220). More importantly, significant OS benefit was detected in ITH-low SCLC patients in comparison with ITH-high ones (P = 0.0049). ITH was an independent prognostic factor on OS with clinicopathological variables adjusted (HR, 2.044; 95% CI 1.190-3.512; P = 0.010). We also demonstrated significantly different driver genes and CNV between ITH-low and ITH-high SCLC.

CONCLUSION

Our work pointed the negative association of ITH with CD8⁺ T cell infiltration and suggested ITH as a potential predictor of OS in SCLC, putting forward a direction for more precise and individualized therapeutic strategies for SCLC.

[Pathological features and immune microenvironment in HER-2 intratumoral heterogeneous breast cancers]

Objective: To observe the clinical pathology features, and immune microenvironment of HER-2 intratumoral heterogeneity breast cancer. Methods: Thirty cases of HER-2 intratumoral heterogeneous breast cancer were retrospectively analyzed in Tianjin Medical University Cancer Institute and Hospital from November 2017 to June 2020. HER-2 expression was detected by immunohistochemistry and verified by dual color silver-enhanced in-situ hybridization (D-SISH). HER-2 intratumoral positive and negative regions were divided. The pathological characteristics, subtype, and the level of tumor infiltrating lymphocytes (TILs) and the expression of programmed cell death-ligand 1 (PD-L1) were evaluated respectively. Results: The proportion of HER-2 positive cells of the breast cancer ranged from 10% to 90%. The pathological type was mainly invasive non-special typecarcinoma. Six cases presented different pathological types between HER-2 positive and negative regions. The HER-2-positive areas included 2 cases of carcinoma with apocrine differentiation, and the negative areas included 2 cases of invasive micropapillary carcinoma, 1 case of invasive papillary carcinoma, and 1 case of carcinoma with apocrine differentiation. In HER-2 positive regions, 17 cases were Luminal B and 13 cases were HER-2 overexpressed types. There were 22 cases of Luminal B and 8 cases of triple negative tumors in the HER-2 negative areas. The levels of TILs in HER-2 positive and negative areas accounted for 53.3% (16/30) and 26.7% (8/30), respectively, with a statistically significant difference (P=0.035). The positive expression of PD-L1 in HER-2 positive area and HER-2 negative area were 6 cases and 9 cases, respectively. Among 8 cases with HER-2 negative regions containing triple negative components, 4 cases were positive for PD-L1 expression. Conclusions: In the case of HER-2 intratumoral heterogeneity, it is necessary to pay attention to both HER-2 positive and negative regions, and evaluate subtype separately as far as possible. For HER-2 intratumoral heterogeneous breast cancer containing triple negative components, the treatment mode can be optimized by refining the intratumoral expression of PD-L1.

BRAFV600E Expression Is Homogenous and Associated with Nonrecurrent Disease and Better Survival in Primary Melanoma

BACKGROUND

Superficial spreading melanomas (SSMs) are the most common type of melanoma and cause the majority of skin cancer deaths. More than 50% of cases harbor a mutation in the BRAF gene that activates the mitogen-activated protein kinase (MAPK) cancer signaling pathway. BRAFV600E is the most common BRAF mutation, and it represents an important biomarker that guides treatment selection. However, the relationship between the BRAFV600E gene expression and intratumoral protein distribution, on one side, and clinicopathological factors and patient outcomes, on the other, is not fully described. Additionally, whether MAPK cancer signaling activation in melanoma is due to increased biochemical activity of BRAFV600E, increased mRNA levels, or both requires further investigation. Here, we addressed these questions by examining expression patterns of BRAFV600E in primary treatment-naive melanomas and correlating them to clinicopathological factors and patient outcomes.

METHODS

In 166 SSM cases, we performed immunohistochemical staining to investigate the protein expression of BRAFV600E, and we measured BRAF mRNA levels using NanoString nCounter system.

RESULTS

Ninety-seven (49%) melanomas stained positive for BRAFV600E, with nearly 100% intratumoral homogeneity observed. Positive BRAFV600E expression was significantly associated with nonrecurrent disease and was found to be an independent predictor of better prognosis in univariate and multivariable analyses. Furthermore, presence of tumor-infiltrating lymphocytes, sentinel lymph node biopsy negativity, and low Breslow thickness were all independent predictors of better prognosis. We observed no difference in the BRAF mRNA levels in BRAFV600E-negative and BRAFV600E-positive melanomas, respectively. Validation in a larger publicly available cohort confirmed that there is only a weak correlation (Spearman 0.4) between BRAFV600E mRNA and protein levels and no differences in mRNA between BRAFV600E mutated and non-mutated patients.

CONCLUSION

Our findings indicated that BRAFV600E is homogeneously present throughout the whole tumor and is associated with nonrecurrent disease and better survival in primary melanoma. We also showed that BRAFV600E mutation does not result in higher transcriptional levels, suggesting that activation of the MAPK signaling pathway in BRAFV600E mutated patients can be attributed to the increased biochemical activity caused by the mutation.

Multi-region sequencing depicts intratumor heterogeneity and clonal evolution in cervical cancer

Cervical cancer is a heterogeneous malignancy mainly caused by human papillomavirus (HPV). While a few studies have revealed heterogeneity of cervical cancer in chromosome levels, the correlation between genetic heterogeneity and HPV integration in cervical cancer remains unknown. Here, we applied multi-region whole-exome sequencing and HPV integration analysis to explore intratumor heterogeneity in cervical cancer. We sequenced 20 tumor regions and 5 adjacent normal tissues from 5 cervical cancer patients, analysis based on somatic mutations and somatic copy number alterations (SCNAs) levels were performed. Variable heterogeneity was observed between the five patients with different tumor stages and HPV infection statuses. We found HPV integration has a positive effect on somatic mutation burden, but the relation to SCNAs remains unclear. Frequently mutated genes in cervical cancer were identified as trunk events, such as FBXW7, PIK3CA, FAT1 in somatic mutations and TP63, MECOM, PIK3CA, TBL1XR1 in SCNAs. New potential driver genes in cervical cancer were summarized including POU2F2, TCF7 and UBE2A. The SCNAs level has potential relation with tumor stage, and Signature 3 related to homologous recombination deficiency may be the appropriate biomarker in advanced cervical cancer. Mutation signature analysis also revealed a potential pattern that APOBEC-associated signature occurs in early stage and signatures associated with DNA damage repair arise at the later stage of cervical cancer evolution. In a conclusion, our study provides insights into the potential relationship between HPV infection and tumor heterogeneity. Those results enhanced our understanding of tumorigenesis and progression in cervical cancer.

Transcriptomic intratumor heterogeneity of breast cancer patient-derived organoids may reflect the unique biological features of the tumor of origin

BACKGROUND

The intratumor heterogeneity (ITH) of cancer cells plays an important role in breast cancer resistance and recurrence. To develop better therapeutic strategies, it is necessary to understand the molecular mechanisms underlying ITH and their functional significance. Patient-derived organoids (PDOs) have recently been utilized in cancer research. They can also be used to study ITH as cancer cell diversity is thought to be maintained within the organoid line. However, no reports investigated intratumor transcriptomic heterogeneity in organoids derived from patients with breast cancer. This study aimed to investigate transcriptomic ITH in breast cancer PDOs.

METHODS

We established PDO lines from ten patients with breast cancer and performed single-cell transcriptomic analysis. First, we clustered cancer cells for each PDO using the Seurat package. Then, we defined and compared the cluster-specific gene signature (ClustGS) corresponding to each cell cluster in each PDO.

RESULTS

Cancer cells were clustered into 3-6 cell populations with distinct cellular states in each PDO line. We identified 38 clusters with ClustGS in 10 PDO lines and used Jaccard similarity index to compare the similarity of these signatures. We found that 29 signatures could be categorized into 7 shared meta-ClustGSs, such as those related to the cell cycle or epithelial-mesenchymal transition, and 9 signatures were unique to single PDO lines. These unique cell populations appeared to represent the characteristics of the original tumors derived from patients.

CONCLUSIONS

We confirmed the existence of transcriptomic ITH in breast cancer PDOs. Some cellular states were commonly observed in multiple PDOs, whereas others were specific to single PDO lines. The combination of these shared and unique cellular states formed the ITH of each PDO.

CT-based radiogenomic analysis dissects intratumor heterogeneity and predicts prognosis of colorectal cancer: a multi-institutional retrospective study

BACKGROUND

This study aimed to develop a radiogenomic prognostic prediction model for colorectal cancer (CRC) by investigating the biological and clinical relevance of intratumoural heterogeneity.

METHODS

This retrospective multi-cohort study was conducted in three steps. First, we identified genomic subclones using unsupervised deconvolution analysis. Second, we established radiogenomic signatures to link radiomic features with prognostic subclone compositions in an independent radiogenomic dataset containing matched imaging and gene expression data. Finally, the prognostic value of the identified radiogenomic signatures was validated using two testing datasets containing imaging and survival information collected from separate medical centres.

RESULTS

This multi-institutional retrospective study included 1601 patients (714 females and 887 males; mean age, 65 years ± 14 [standard deviation]) with CRC from 5 datasets. Molecular heterogeneity was identified using unsupervised deconvolution analysis of gene expression data. The relative prevalence of the two subclones associated with cell cycle and extracellular matrix pathways identified patients with significantly different survival outcomes. A radiogenomic signature-based predictive model significantly stratified patients into high- and low-risk groups with disparate disease-free survival (HR = 1.74, P = 0.003). Radiogenomic signatures were revealed as an independent predictive factor for CRC by multivariable analysis (HR = 1.59, 95% CI:1.03-2.45, P = 0.034). Functional analysis demonstrated that the 11 radiogenomic signatures were predominantly associated with extracellular matrix and immune-related pathways.

CONCLUSIONS

The identified radiogenomic signatures might be a surrogate for genomic signatures and could complement the current prognostic strategies.

MEDICC2: whole-genome doubling aware copy-number phylogenies for cancer evolution

Aneuploidy, chromosomal instability, somatic copy-number alterations, and whole-genome doubling (WGD) play key roles in cancer evolution and provide information for the complex task of phylogenetic inference. We present MEDICC2, a method for inferring evolutionary trees and WGD using haplotype-specific somatic copy-number alterations from single-cell or bulk data. MEDICC2 eschews simplifications such as the infinite sites assumption, allowing multiple mutations and parallel evolution, and does not treat adjacent loci as independent, allowing overlapping copy-number events. Using simulations and multiple data types from 2780 tumors, we use MEDICC2 to demonstrate accurate inference of phylogenies, clonal and subclonal WGD, and ancestral copy-number states.

Colon cancer organoids using monoclonal organoids established in four different lesions of one cancer patient reveal tumor heterogeneity and different real-time responsiveness to anti-cancer drugs

Organoid culture technique has been taking center stage as a next-generation ex-vivo model due to advancement of stem cell research techniques. The importance of the laboratory-based ex vivo model has increasingly been recognized for recapitulating histological, and physioglocal conditions of in vivo microenviorment. Accordingly, the use of this technique has also broadened the understanding of intratumoral heterogeneity which is closely associated with varied drug responses observed in patients. Likewise, studies on heterogeneity within a single tumor tissue have drawn much attention. Here, we isolated 15 single clones from 4 tumor organoid lines from 1 patient at a primary passage from one patient. Each organoid line showed variable alterations in both genotype and phenotype. Furthermore, our methodological approach on drug test employing a high-throughput screening system enabled us to pinpoint the optimal time frame for anti-cancer drugs within a single tumor. We propose that our method can effectively reveal the heterogeneity of time-point in drug response, and the most optimal therapeutic strategies for individual patient.

DEPTH2: an mRNA-based algorithm to evaluate intratumor heterogeneity without reference to normal controls

Background

Intratumor heterogeneity (ITH) is associated with tumor progression, unfavorable prognosis, immunosuppression, genomic instability, and therapeutic resistance. Thus, evaluation of ITH levels is valuable in cancer diagnosis and treatment.

Methods

We proposed a new mRNA-based ITH evaluation algorithm (DEPTH2) without reference to normal controls. DEPTH2 evaluates ITH levels based on the standard deviations of absolute z-scored transcriptome levels in tumors, reflecting the asynchronous level of transcriptome alterations relative to the central tendency in a tumor.

Results

By analyzing 33 TCGA cancer types, we demonstrated that DEPTH2 ITH was effective in measuring ITH for its significant associations with tumor progression, unfavorable prognosis, genomic instability, reduced antitumor immunity and immunotherapy response, and altered drug response in diverse cancers. Compared to other five ITH evaluation algorithms (MATH, PhyloWGS, ABSOLUTE, DEPTH, and tITH), DEPTH2 ITH showed a stronger association with unfavorable clinical outcomes, and in characterizing other properties of ITH, such as its associations with genomic instability and antitumor immunosuppression, DEPTH2 also displayed competitive performance.

Conclusions

DEPTH2 is expected to have a wider spectrum of applications in evaluating ITH in comparison to other algorithms.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-022-03355-1.

Impact of cancer metabolism on therapy resistance - Clinical implications

Despite an increasing arsenal of anticancer therapies, many patients continue to have poor outcomes due to the therapeutic failures and tumor relapses. Indeed, the clinical efficacy of anticancer therapies is markedly limited by intrinsic and/or acquired resistance mechanisms that can occur in any tumor type and with any treatment. Thus, there is an urgent clinical need to implement fundamental changes in the tumor treatment paradigm by the development of new experimental strategies that can help to predict the occurrence of clinical drug resistance and to identify alternative therapeutic options. Apart from mutation-driven resistance mechanisms, tumor microenvironment (TME) conditions generate an intratumoral phenotypic heterogeneity that supports disease progression and dismal outcomes. Tumor cell metabolism is a prototypical example of dynamic, heterogeneous, and adaptive phenotypic trait, resulting from the combination of intrinsic [(epi)genetic changes, tissue of origin and differentiation dependency] and extrinsic (oxygen and nutrient availability, metabolic interactions within the TME) factors, enabling cancer cells to survive, metastasize and develop resistance to anticancer therapies. In this review, we summarize the current knowledge regarding metabolism-based mechanisms conferring adaptive resistance to chemo-, radio-and immunotherapies as well as targeted therapies. Furthermore, we report the role of TME-mediated intratumoral metabolic heterogeneity in therapy resistance and how adaptations in amino acid, glucose, and lipid metabolism support the growth of therapy-resistant cancers and/or cellular subpopulations. We also report the intricate interplay between tumor signaling and metabolic pathways in cancer cells and discuss how manipulating key metabolic enzymes and/or providing dietary changes may help to eradicate relapse-sustaining cancer cells. Finally, in the current era of personalized medicine, we describe the strategies that may be applied to implement metabolic profiling for tumor imaging, biomarker identification, selection of tailored treatments and monitoring therapy response during the clinical management of cancer patients.

Intratumor heterogeneity and clonal evolution revealed in castration-resistant prostate cancer by longitudinal genomic analysis

Intratumor heterogeneity is a key driver for local relapse and treatment failure. Thus, using multifocal prostate cancer as a model to investigate tumor inter-clonal relationships and tumor evolution could aid in our understanding of drug resistance. Previous studies discovered genomic alterations by comparing hormone-sensitive prostate cancer (HSPC) with castration-resistant prostate cancer (CRPC) in large cohorts. However, most studies did not sequentially sample tumors from the same patient. In our study, we performed whole-exome sequencing (WES) on 14 specimens from five locally relapsed patients before and after androgen-deprivation therapy. We described the landscape of genomic alterations before and after treatment and identified critical driver events that could have contributed to the evolution of CRPC. In addition to confirming known cancer genes such as TP53 and CDK12, we also identified new candidate genes that may play a role in the progression of prostate cancer, including MYO15A, CHD6 and LZTR1. At copy number alteration (CNA) level, gain of 8q24.13-8q24.3 was observed in 60% of patients and was the most commonly altered locus in both HSPC and CRPC tumors. Finally, utilizing phylogenetic reconstruction, we explored the clonal progression pattern from HSPC to CRPC in each patient. Our findings highlight the complex and heterogeneous mechanisms underlying the development of drug resistance, and underscore the potential value of monitoring tumor clonal architectures during disease progression in a clinical setting.

Heterogeneous microenvironmental stiffness regulates pro-metastatic functions of breast cancer cells

Besides molecular and phenotypic variations observed in cancer cells, intratumoral heterogeneity also occurs in the tumor microenvironment. Correlative stiffness maps of different intratumor locations in breast tumor biopsies show that stiffness increases from core to periphery. However, how different local ECM stiffness regulates key functions of cancer cells in tumor progression remains unclear. Although increased tissue stiffness is an established driver of breast cancer progression, conclusions from 2D cultures do not correspond with newer data from cancer cells in 3D environments. Many past studies of breast cancer in 3D culture fail to recapitulate the stiffness of a real breast tumor or the various local stiffnesses present in a tumor microenvironment. In this study, we developed a series of collagen/alginate hybrid hydrogels with adjustable stiffness to match the core, middle, and peripheral zones of a breast tumor. We used this hydrogel system to investigate effects of different local stiffness on morphology, proliferation, and migration of breast cancer cells. RNA sequencing of cells in hydrogels with different stiffness revealed changes in multiple cellular processes underlying cancer progression, including angiogenesis and metabolism. We discovered that tumor cells in a soft environment enriched YAP1 and AP1 signaling related genes, whereas tumor cells in a stiff environment became more pro-angiogenic by upregulating fibronectin 1 (FN1) and matrix metalloproteinase 9 (MMP9) expression. This systematic study defines how the range of environmental stiffnesses present in a breast tumor regulates cancer cells, providing new insights into tumorigenesis and disease progression at the tumor-stroma interface. STATEMENT OF SIGNIFICANCE: Applied a well-defined hybrid hydrogel system to mimic the tumor microenvironment with heterogeneous local stiffness. Breast cancer cells tended to proliferate in soft core environment while migrate in stiff peripheral environment. Breast cancer cells shift from glycolysis to OXPHOS and fatty acid metabolism responding to stiff matrix microenvironment. The transcriptomic profile of breast cancer cells altered due to microenvironmental stiffness changes.

Evolutionary Mechanisms of Cancer Suggest Rational Therapeutic Approaches

The goal in personalized therapeutic approaches for cancer medicine is to identify specific mutations with prognostic and therapeutic value in order to tailor the therapy for the single patient. The most powerful obstacle for personalized medicine arises from intratumor heterogeneity and clonal evolution, which can promote drug resistance. In this scenario, new technologies, such as next-generation sequencing, have emerged as a central diagnostic tool to profile cancer (epi)genomic landscapes. Therefore, a better understanding of the biological mechanisms underlying cancer evolution is mandatory and represents the current challenge to accurately predict whether cancer will recur after chemotherapy with the aim to tailor rational therapeutic approaches.

Spatially resolved metabolomic characterization of muscle invasive bladder cancer by mass spectrometry imaging

INTRODUCTION

Muscle invasive bladder cancer (MIBC) is an advanced stage of bladder cancer which poses a severe threat to life. Cancer development is usually accompanied by remarkable alterations in cell metabolism, and hence deep insights into MIBC at the metabolomic level can facilitate the understanding of the biochemical mechanisms involved in the cancer development and progression.

METHODS

In this proof-of-concept study, the optimal cutting temperature (OCT)-embedded MIBC samples were first washed with pure water to remove the polymer compounds which could cause severe signal suppression during mass spectrometry. Further, the tissue sections were analyzed by infrared matrix-assisted laser desorption electrospray ionization mass spectrometry imaging (IR-MALDESI MSI), providing an overview on the spatially resolved metabolomic profiles.

RESULTS

The MSI data enabled the discrimination between not only the cancerous and normal tissues, but also the subregions within a tissue section associated with different disease states. Using t-Distributed Stochastic Neighbor Embedding (t-SNE), the hyperdimensional MSI data was mapped into a two-dimensional space to visualize the spectral similarity, providing evidence that metabolomic alterations might have occurred outside the histopathological tumor border. Least absolute shrinkage and selection operator (LASSO) was further employed to classify sample pathology in a pixel-wise manner, yielding excellent prediction sensitivity and specificity up to 96% based on the statistically characteristic spectral features.

CONCLUSION

The results demonstrate great promise of IR-MALDESI MSI to identify molecular changes derived from cancer and unveil tumor heterogeneity, which can potentially promote the discovery of clinically relevant biomarkers and allow for applications in precision medicine.

Translation of single-cell transcriptomic analysis of uveal melanomas to clinical oncology

Uveal melanoma (UM) is an aggressive and deadly neoplasm. In recent decades, great efforts have been made to obtain a more comprehensive understanding of genetics, genomics and molecular changes in UM, enabling the identification of key cellular processes and signalling pathways. Still, there is no effective treatment for the metastatic disease. Intratumoural heterogeneity (ITH) is thought to be one of the leading determinants of metastasis, therapeutic resistance and recurrence. Crucially, tumours are complex ecosystems, where cancer cells, and diverse cell types from their microenvironment engage in dynamic spatiotemporal crosstalk that allows cancer progression, adaptation and evolution. This highlights the urgent need to gain insight into ITH in UM and its intersection with the microenvironment to overcome treatment failure. Here we provide an overview of the studies and technologies to study ITH in human UMs and tumour micro-environmental composition. We discuss how to incorporate ITH into clinical consideration for the purpose of advocating for new clinical management. We focus on the application of single-cell transcriptomic analysis and propose that understanding the driving forces and functional consequences of the observed tumour heterogeneity holds promise for changing the treatment paradigm of metastatic UMs, surmounting resistance and improving patient prognosis.

A subcentimeter duodenal neuroendocrine neoplasm with a liver metastasis upgraded to G3: a case report

BACKGROUND

Although duodenal neuroendocrine neoplasms (DuNENs) usually have indolent phenotypes, some DuNENs exhibit aggressive clinical manifestations. Tumor size > 1 cm, lymph node metastasis, and high grade have been associated with poor prognosis. However, preoperative risk evaluation is often difficult, because Ki-67 index on biopsy is frequently underestimated due to the intratumor heterogeneity. Here, we present a case of a subcentimeter DuNEN with a low Ki-67 index on endoscopic biopsy, who developed lymph node metastasis and high-grade liver metastasis.

CASE PRESENTATION

The patient was a 52-year-old female who presented an epigastric pain. Esophagogastroduodenoscopy revealed a duodenal submucosal lesion with a size of 8 mm. The endoscopic biopsy showed DuNEN with a Ki-67 index of 3.3% (G2 categorized by the World Health Organization 2019 classification). We performed an open partial duodenectomy with adjacent lymph node dissection. Pathological examination of the resected specimens revealed a Ki-67 index of 13.5% (G2) in the "hot spot" and lymph node metastasis. A hepatic low-density area detected on preoperative contrast-enhanced computed tomography appeared to be a liver metastasis on postoperative gadoxetic acid-enhanced magnetic resonance imaging. Subsequently, we performed a laparoscopic partial hepatectomy. Pathological examination of the liver specimen showed a metastatic neuroendocrine tumor with a Ki-67 index of 27.5% (NET-G3). The patient has been alive for 14 months since the hepatectomy.

CONCLUSIONS

This case shows the possibility of high malignant potential of DuNEN even if the primary lesion is < 1 cm and has a low Ki-67 index on biopsy.

Functional 4-D clustering for characterizing intratumor heterogeneity in dynamic imaging: evaluation in FDG PET as a prognostic biomarker for breast cancer

Purpose

Probe-based dynamic (4-D) imaging modalities capture breast intratumor heterogeneity both spatially and kinetically. Characterizing heterogeneity through tumor sub-populations with distinct functional behavior may elucidate tumor biology to improve targeted therapy specificity and enable precision clinical decision making.

Methods

We propose an unsupervised clustering algorithm for 4-D imaging that integrates Markov-Random Field (MRF) image segmentation with time-series analysis to characterize kinetic intratumor heterogeneity. We applied this to dynamic FDG PET scans by identifying distinct time-activity curve (TAC) profiles with spatial proximity constraints. We first evaluated algorithm performance using simulated dynamic data. We then applied our algorithm to a dataset of 50 women with locally advanced breast cancer imaged by dynamic FDG PET prior to treatment and followed to monitor for disease recurrence. A functional tumor heterogeneity (FTH) signature was then extracted from functionally distinct sub-regions within each tumor. Cross-validated time-to-event analysis was performed to assess the prognostic value of FTH signatures compared to established histopathological and kinetic prognostic markers.

Results

Adding FTH signatures to a baseline model of known predictors of disease recurrence and established FDG PET uptake and kinetic markers improved the concordance statistic (C-statistic) from 0.59 to 0.74 (p = 0.005). Unsupervised hierarchical clustering of the FTH signatures identified two significant (p < 0.001) phenotypes of tumor heterogeneity corresponding to high and low FTH. Distributions of FDG flux, or Ki, were significantly different (p = 0.04) across the two phenotypes.

Conclusions

Our findings suggest that imaging markers of FTH add independent value beyond standard PET imaging metrics in predicting recurrence-free survival in breast cancer and thus merit further study.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00259-021-05265-8.

Application of single-cell sequencing technologies in pancreatic cancer

Pancreatic cancer (PC) is the third lethal disease for cancer-related mortalities globally. This is mainly because of the aggressive nature and heterogeneity of the disease that is diagnosed only in their advanced stages. Thus, it is challenging for researchers and clinicians to study the molecular mechanism involved in the development of this aggressive disease. The single-cell sequencing technology enables researchers to study each and every individual cell in a single tumor. It can be used to detect genome, transcriptome, and multi-omics of single cells. The current single-cell sequencing technology is now becoming an important tool for the biological analysis of cells, to find evolutionary relationship between multiple cells and unmask the heterogeneity present in the tumor cells. Moreover, its sensitivity nature is found progressive enabling to detect rare cancer cells, circulating tumor cells, metastatic cells, and analyze the intratumor heterogeneity. Furthermore, these single-cell sequencing technologies also promoted personalized treatment strategies and next-generation sequencing to predict the disease. In this review, we have focused on the applications of single-cell sequencing technology in identifying cancer-associated cells like cancer-associated fibroblast via detecting circulating tumor cells. We also included advanced technologies involved in single-cell sequencing and their advantages. The future research indeed brings the single-cell sequencing into the clinical arena and thus could be beneficial for diagnosis and therapy of PC patients.

Morphological intratumor heterogeneity in ductal carcinoma in situ of the breast

Ductal carcinoma in situ (DCIS) of the breast is a heterogeneous disease in terms of morphological characteristics, protein expression profiles, genetic abnormalities, and potential for progression. Molecular heterogeneity has been extensively studied in DCIS. Yet morphological heterogeneity remains relatively undefined. This study investigated morphological intratumor heterogeneity in a series of 51 large DCIS. Nuclear atypia, DCIS architecture, necrosis, calcifications, stromal architecture, and stromal inflammation were assessed in one biopsy slide and three representative slides from each corresponding resection. For each histopathological feature, a histo-score was determined per slide and compared between the biopsy and the resection, as well as within a single resection. Statistical analysis comprised of Friedman tests, post hoc Wilcoxon tests with Bonferroni corrections, Mann-Whitney U tests, and chi-square tests. Despite substantial morphological heterogeneity in around 50% of DCIS, the histopathological assessment of the biopsy did not statistically significantly differ from the resection. Morphological heterogeneity was not significantly associated with patient age, DCIS size, or type of surgery, except for a weak association between heterogeneous stromal inflammation and smaller DCIS size. At the group level, the degree of heterogeneity did not significantly affect the representativity of a biopsy. At the individual patient level, however, the presence of necrosis, intraductal calcifications, myxoid stromal changes, and high-grade nuclear atypia was underestimated in a minority of DCIS patients. This study confirms the presence of morphological heterogeneity in DCIS for all six evaluated histopathological features. This should be kept in mind when taking biopsy-based treatment decisions for DCIS patients.

Detection of glioblastoma intratumor heterogeneity in radiosensitivity using patient-derived neurosphere cultures

PURPOSE

Glioblastoma (GBM) is characterized by extensive clonal diversity suggesting the presence of tumor cells with varying degrees of treatment sensitivity. Radiotherapy is an integral part of glioblastoma treatment. Whether GBMs are comprised of spatially distinct cellular populations with uniform or varying degrees of radiosensitivity has not been established.

METHODS

Spatially distinct regions of three GBMs (J3, J7 and J14) were resected and unique cell lines were derived from each region. DNA from cell lines, corresponding tumor fragments, and patient blood was extracted for whole exome sequencing. Variants, clonal composition, and functional implications were compared and analyzed with superFreq and IPA. Limiting dilution assays were performed on cell lines to measure intrinsic radiosensitivity.

RESULTS

Based on WES, cell lines generated from different regions of the same tumor were more closely correlated with their tumor of origin than the other GBMs. Variant and clonal composition comparisons showed that cell lines from distinct tumors displayed increasing levels of ITH with J3 and J14 having the lowest and highest, respectively. The radiosensitivities of the cell lines generated from the J3 tumor were similar as were those generated from the J7 tumor. However, the radiosensitivities of the 2 cell lines generated from the J14 tumor (J14T3 and J14T6) were significantly different with J14T6 being more sensitive than J14T3.

CONCLUSION

Data suggest a tumor dependent ITH in radiosensitivity. The existence of ITH in radiosensitivity may impact not only the initial therapeutic response but also the effectiveness of retreatment protocols.

Multiregional sequence revealed SMARCA4 R1192C mutant clones acquired EGFR C797S mutation in the metastatic site of an EGFR-mutated NSCLC patient

OBJECTIVES

Intratumor heterogeneity (ITH) is reportedly involved in the clinical course and in the response to treatment, although the detailed mechanism underlying this effect remains unclear. In this study, we investigated the effect of epithelial growth factor receptor-tyrosine kinase inhibitor (EGFR-TKI) treatment on ITH with an EGFR-mutated lung cancer patient using the multiregional sequence (MRS) analysis of surgical specimens both before and after EGFR-TKI treatment.

MATERIALS AND METHODS

We performed the MRS analysis of primary lung and resistant metastatic lesions, respectively through targeted sequencing, covering whole exons of 53 significantly mutated, lung cancer-associated genes. Through the comparison of primary lung and metastatic lesion mutation profiles, along with PyClone analysis of sequence data, we revealed the trajectory of resistant clones from a primary to metastatic site.

RESULTS

MRS revealed high ITH at the primary lung lesion and low ITH at the metastatic site, suggesting that the EGFR-TKI treatment followed an attenuated progression pattern. Tumor cell clones harboring EGFR G719S, L861R, SMARCA4 R1192C and KMT2D Q1139R mutations in the primary lesion metastasized and acquired the EGFR-TKI-resistant EGFR C797S mutation.

CONCLUSION

MRS revealed attenuated progression pattern and clonal evolution. In the case of high ITH with attenuated progression pattern, as observed in the present case, local treatment may be effective when oligometastasis emerged.

Reliability of a single-region sample to evaluate tumor immune microenvironment in hepatocellular carcinoma

BACKGROUND & AIMS

Intratumor heterogeneity has frequently been reported in patients with hepatocellular carcinoma (HCC). Thus, the reliability of single-region tumor samples for evaluation of the tumor immune microenvironment is also debatable. We conducted a prospective study to analyze the similarity in tumor immune microenvironments among different regions of a single tumor.

METHODS

Multi-region sampling was performed on newly resected tumors. The tumor immune microenvironment was evaluated by immunohistochemical staining of PD-L1, CD4, CD8, CD20, FoxP3, DC-LAMP (or LAMP3), CD68, MPO, and tertiary lymphoid structures (TLSs). PD-L1 expression was manually quantified according to the percentage of PD-L1-stained tumor or stromal cells. The densities (number/mm²) of immune cells and the number of TLSs per sample were determined by whole-section counting. RNA-sequencing was applied in selected samples. Similarities in tumor immune microenvironments within each tumor were evaluated by multivariate Mahalanobis distance analyses.

RESULTS

Thirteen tumors were collected from 12 patients. The median diameter of tumors was 9 cm (range 3-16 cm). A median of 6 samples (range 3-12) were obtained from each tumor. Nine (69.2%) tumors exhibited uniform expression of PD-L1 in all regions of the tumor. Out of 13 tumors analyzed by immunohistochemical staining, 8 (61.5%) tumors displayed a narrow Mahalanobis distance for all regions within the tumor; while 8 (66.7%) of the 12 tumors analyzed by RNA-sequencing displayed a narrow Mahalanobis distance. Immunohistochemistry and RNA-sequencing had a high concordance rate (83.3%; 10 of 12 tumors) for the evaluation of similarities between tumor immune microenvironments within a tumor.

CONCLUSIONS

A single-region tumor sample might be reliable for the evaluation of tumor immune microenvironments in approximately 60-70% of patients with HCC.

LAY SUMMARY

Heterogeneity in the regional immune microenvironments of tumors has been reported in patients with hepatocellular carcinoma. This heterogeneity could be an obstacle when trying to reliably evaluate the immune microenvironment of an entire tumor using only a single-region tumor sample, which may be the only option in patients with more advanced disease. Our study utilized both immunohistochemical and transcriptomic analyses to demonstrate that a single-region sample is reliable for evaluation of tumor immune microenvironments in 60-70% of patients with hepatocellular carcinoma.

Clinical implications of intratumor heterogeneity: challenges and opportunities

In this review, we highlight the role of intratumoral heterogeneity, focusing on the clinical and biological ramifications this phenomenon poses. Intratumoral heterogeneity arises through complex genetic, epigenetic, and protein modifications that drive phenotypic selection in response to environmental pressures. Functionally, heterogeneity provides tumors with significant adaptability. This ranges from mutual beneficial cooperation between cells, which nurture features such as growth and metastasis, to the narrow escape and survival of clonal cell populations that have adapted to thrive under specific conditions such as hypoxia or chemotherapy. These dynamic intercellular interplays are guided by a Darwinian selection landscape between clonal tumor cell populations and the tumor microenvironment. Understanding the involved drivers and functional consequences of such tumor heterogeneity is challenging but also promises to provide novel insight needed to confront the problem of therapeutic resistance in tumors.

In Silico implementation of evolutionary paradigm in therapy design: Towards anti-cancer therapy as Darwinian process

In here presented in silico study we suggest a way how to implement the evolutionary principles into anti-cancer therapy design. We hypothesize that instead of its ongoing supervised adaptation, the therapy may be constructed as a self-sustaining evolutionary process in a dynamic fitness landscape established implicitly by evolving cancer cells, microenvironment and the therapy itself. For these purposes, we replace a unified therapy with the 'therapy species', which is a population of heterogeneous elementary therapies, and propose a way how to turn the toxicity of the elementary therapy into its fitness in a way conforming to evolutionary causation. As a result, not only the therapies govern the evolution of different cell phenotypes, but the cells' resistances govern the evolution of the therapies as well. We illustrate the approach by the minimalistic ad hoc evolutionary model. Its results indicate that the resistant cells could bias the evolution towards more toxic elementary therapies by inhibiting the less toxic ones. As the evolutionary causation of cancer drug resistance has been intensively studied for a few decades, we refer to cancer as a special case to illustrate purely theoretical analysis.

DENDRO: genetic heterogeneity profiling and subclone detection by single-cell RNA sequencing

Although scRNA-seq is now ubiquitously adopted in studies of intratumor heterogeneity, detection of somatic mutations and inference of clonal membership from scRNA-seq is currently unreliable. We propose DENDRO, an analysis method for scRNA-seq data that clusters single cells into genetically distinct subclones and reconstructs the phylogenetic tree relating the subclones. DENDRO utilizes transcribed point mutations and accounts for technical noise and expression stochasticity. We benchmark DENDRO and demonstrate its application on simulation data and real data from three cancer types. In particular, on a mouse melanoma model in response to immunotherapy, DENDRO delineates the role of neoantigens in treatment response.

Circulating Tumor Cells: High-Throughput Imaging of CTCs and Bioinformatic Analysis

Circulating tumor cells (CTCs) represent novel biomarkers, since they are obtainable through a simple and noninvasive blood draw or liquid biopsy. Here, we review the high-definition single-cell analysis (HD-SCA) workflow, which brings together modern methods of immunofluorescence with more sophisticated image processing to rapidly and accurately detect rare tumor cells among the milieu of platelets, erythrocytes, and leukocytes in the peripheral blood. In particular, we discuss progress in methods to measure CTC morphology and subcellular protein expression, and we highlight some initial applications that lead to fundamental new insights about the hematogenous phase of cancer, as well as its performance in early-stage diagnosis and treatment monitoring. We end with an outlook on how to further probe CTCs and the unique advantages of the HD-SCA workflow for improving the precision of cancer care.

A rewiring model of intratumoral interaction networks

Intratumoral heterogeneity (ITH) has been regarded as a key cause of the failure and resistance of cancer therapy, but how it behaves and functions remains unclear. Advances in single-cell analysis have facilitated the collection of a massive amount of data about genetic and molecular states of individual cancer cells, providing a fuel to dissect the mechanistic organization of ITH at the molecular, metabolic and positional level. Taking advantage of these data, we propose a computational model to rewire up a topological network of cell–cell interdependences and interactions that operate within a tumor mass. The model is grounded on the premise of game theory that each interactive cell (player) strives to maximize its fitness by pursuing a “rational self-interest” strategy, war or peace, in a way that senses and alters other cells to respond properly. By integrating this idea with genome-wide association studies for intratumoral cells, the model is equipped with a capacity to visualize, annotate and quantify how somatic mutations mediate ITH and the network of intratumoral interactions. Taken together, the model provides a topological flow by which cancer cells within a tumor cooperate or compete with each other to downstream pathogenesis. This topological flow can be potentially used as a blueprint for genetically intervening the pattern and strength of cell–cell interactions towards cancer control.

Molecular Heterogeneity of Papillary Thyroid Cancer: Comparison of Primary Tumors and Synchronous Metastases in Regional Lymph Nodes by Mass Spectrometry Imaging

Intra-tumor heterogeneity results from both genetic heterogeneity of cancer (sub)clones and phenotypic plasticity of cancer cells that could be induced by different local microenvironments. Here, we used mass spectrometry imaging (MSI) to compare molecular profiles of primary tumors located in the thyroid gland and their synchronous metastases in regional lymph nodes to analyze phenotypic heterogeneity in papillary thyroid cancer. Two types of cancerous (primary tumor and metastasis) and two types of not cancerous (thyroid gland and lymph node) regions of interest (ROIs) were delineated in postoperative material from 11 patients, then the distribution of tryptic peptides (spectral components) was analyzed by MSI in all tissue regions. Moreover, tryptic peptides identified by shotgun proteomics in corresponding tissue lysates were matched to components detected by MSI to enable their hypothetical protein annotation. Unsupervised segmentation of all cancer ROIs revealed that different clusters dominated in tumor ROIs and metastasis ROIs. The intra-patient similarity between thyroid and tumor ROIs was higher than the intra-patient similarity between tumor and metastasis ROIs. Moreover, the similarity between tumor and its metastasis from the same patients was lower than similarities among tumors and among metastases from different patients (inter-patient similarity was higher for metastasis ROIs than for tumor ROIs). Components differentiating between tumor and its metastases were annotated as proteins involved in the organization of the cytoskeleton and chromatin, as well as proteins involved in immunity-related functions. We concluded that phenotypical heterogeneity between primary tumor and lymph node metastases from the same patient was higher than inter-tumor heterogeneity between primary tumors from different patients.

Epigenetic heterogeneity in cancer

Phenotypic and functional heterogeneity is one of the hallmarks of human cancers. Tumor genotype variations among tumors within different patients are known as interpatient heterogeneity, and variability among multiple tumors of the same type arising in the same patient is referred to as intra-patient heterogeneity. Subpopulations of cancer cells with distinct phenotypic and molecular features within a tumor are called intratumor heterogeneity (ITH). Since Nowell proposed the clonal evolution of tumor cell populations in 1976, tumor heterogeneity, especially ITH, was actively studied. Research has focused on the genetic basis of cancer, particularly mutational activation of oncogenes or inactivation of tumor-suppressor genes (TSGs). The phenomenon of ITH is commonly explained by Darwinian-like clonal evolution of a single tumor. Despite the monoclonal origin of most cancers, new clones arise during tumor progression due to the continuous acquisition of mutations. It is clear that disruption of the "epigenetic machinery" plays an important role in cancer development. Aberrant epigenetic changes occur more frequently than gene mutations in human cancers. The epigenome is at the intersection of the environment and genome. Epigenetic dysregulation occurs in the earliest stage of cancer. The current trend of epigenetic therapy is to use epigenetic drugs to reverse and/or delay future resistance to cancer therapies. A majority of cancer therapies fail to achieve durable responses, which is often attributed to ITH. Epigenetic therapy may reverse drug resistance in heterogeneous cancer. Complete understanding of genetic and epigenetic heterogeneity may assist in designing combinations of targeted therapies based on molecular information extracted from individual tumors.

Heterogeneity of breast cancer: The importance of interaction between different tumor cell populations

INTRODUCTION

Breast cancer is the most common cancer and the second leading cause of cancer-related death in women worldwide. Despite the early detection of breast cancer and increasing knowledge of its biology and chemo-resistance, metastatic breast cancer is largely incurable disease. We provide a review of the intertumor and intratumor heterogeneity, explain the differences between triple-negative breast cancer subtypes. Also, we describe the interaction of breast tumor cells with their microenvironment cells and explain how this interaction contributes to the tumor progression, metastasis formation and resistance to the treatment.

DISCUSSION

One of the main causes that complicate the treatment is tumor heterogeneity. It is observed among patients (intertumor heterogeneity) and in each individual tumor (intratumor heterogeneity). In the case of intratumor heterogeneity, the tumor consists of different phenotypical cell populations. During breast cancer subtype identification, a small piece of solid tumor tissue does not necessarily represent all the tumor composition. Breast tumor cell phenotypical differences may appear due to cell localization in different tumor sites, unique response to the treatment, cell interaction with tumor microenvironment or tumor cell interaction with each other. This heterogeneity may lead to breast cancer aggressiveness and challenging treatment.

CONCLUSION

Understanding the molecular and cellular mechanisms of tumor heterogeneity that are relevant to the development of treatment resistance is a major area of research. Identification of differences between populations and their response to anticancer drugs would help to predict the potential resistance to chemotherapy and thus would help to select the most suitable anticancer treatment.

Spatial and Temporal Heterogeneity of Panel-Based Tumor Mutational Burden in Pulmonary Adenocarcinoma: Separating Biology From Technical Artifacts

BACKGROUND

Tumor mutational burden (TMB) is an emerging biomarker used to identify patients who are more likely to benefit from immuno-oncology therapy. Aside from various unsettled technical aspects, biological variables such as tumor cell content and intratumor heterogeneity may play an important role in determining TMB.

METHODS

TMB estimates were determined applying the TruSight Oncology 500 targeted sequencing panel. Spatial and temporal heterogeneity was analyzed by multiregion sequencing (two to six samples) of 24 pulmonary adenocarcinomas and by sequencing a set of matched primary tumors, locoregional lymph node metastases, and distant metastases in five patients.

RESULTS

On average, a coding region of 1.28 Mbp was covered with a mean read depth of 609x. Manual validation of the mutation-calls confirmed a good performance, but revealed noticeable misclassification during germline filtering. Different regions within a tumor showed considerable spatial TMB variance in 30% (7 of 24) of the cases (maximum difference, 14.13 mut/Mbp). Lymph node-derived TMB was significantly lower (p = 0.016). In 13 cases, distinct mutational profiles were exclusive to different regions of a tumor, leading to higher values for simulated aggregated TMB. Combined, intratumor heterogeneity and the aggregated TMB could result in divergent TMB designation in 17% of the analyzed patients. TMB variation between primary tumor and distant metastases existed but was not profound.

CONCLUSIONS

Our data show that, in addition to technical aspects such as germline filtering, the tumor content and spatially divergent mutational profiles within a tumor are relevant factors influencing TMB estimation, revealing limitations of single-sample-based TMB estimations in a clinical context.

Precise co-registration of mass spectrometry imaging, histology, and laser microdissection-based omics

Mass spectrometry imaging (MSI) is an analytical technique for the unlabeled and multiplex imaging of molecules in biological tissue sections. It therefore enables the spatial and molecular annotations of tissues complementary to histology. It has already been shown that MSI can guide subsequent material isolation technologies such as laser microdissection (LMD) to enable a more in-depth molecular characterization of MSI-highlighted tissue regions. However, with MSI now reaching spatial resolutions at the single-cell scale, there is a need for a precise co-registration between MSI and the LMD. As proof-of-principle, MSI of lipids was performed on a breast cancer tissue followed by a segmentation of the data to detect molecularly distinct segments within its tumor areas. After image processing of the segmentation results, the coordinates of the MSI-detected segments were passed to the LMD system by three co-registration steps. The errors of each co-registration step were quantified and the total error was found to be less than 13 μm. With this link established, MSI data can now accurately guide LMD to excise MSI-defined regions of interest for subsequent extract-based analyses. In our example, the excised tissue material was then subjected to ultrasensitive microproteomics in order to determine predominant molecular mechanisms in each of the MSI-highlighted intratumor segments. This work shows how the strengths of MSI, histology, and extract-based omics can be combined to enable a more comprehensive molecular characterization of in situ biological processes.

[Clinical challenges and implications of intratumor heterogeneity]

Tumors display a high, albeit variable, grade of intratumor heterogeneity, both from a clinical and a morphological viewpoint. Furthermore, recent methods of large-scale molecular analysis demonstrate to what extent tumors can also be heterogeneous from a molecular perspective. This is of paramount importance for patients as it has a great impact on the success of so-called precision therapies and explains the reason for a significant number of therapeutic failures in modern oncology. We present an up-to-date review of the latest findings in a group of tumors with a high social impact, commonly seen in the daily routine of the pathology laboratory.

Differential YAP expression in glioma cells induces cell competition and promotes tumorigenesis

Intratumor heterogeneity associates with cancer progression and may account for a substantial portion of therapeutic resistance. Although extensive studies have focused on the origin of the heterogeneity, biological interactions between heterogeneous malignant cells within a tumor are largely unexplored. Glioblastoma (GBM) is the most aggressive primary brain tumor. Here, we found that the expression of Yes-associated protein (YAP, also known as YAP1) is intratumorally heterogeneous in GBM. In a xenograft mouse model, differential YAP expression in glioma cells promotes tumorigenesis and leads to clonal dominance by cells expressing more YAP. Such clonal dominance also occurs in vitro when cells reach confluence in the two-dimensional culture condition or grow into tumor spheroids. During this process, growth of the dominant cell population is enhanced. In the tumor spheroid, such enhanced growth is accompanied by increased apoptosis in cells expressing less YAP. The cellular interaction during clonal dominance appears to be reminiscent of cell competition. RNA-seq analysis suggests that this interaction induces expression of tumorigenic genes, which may contribute to the enhanced tumor growth. These results suggest that tumorigenesis benefits from competitive interactions between heterogeneous tumor cells.

Intratumor heterogeneity comparison among different subtypes of non-small-cell lung cancer through multi-region tissue and matched ctDNA sequencing

Understanding of intratumor heterogeneity (ITH) among different non-small cell lung cancer (NSCLC) subtypes is necessary. Whether circulating tumor DNA (ctDNA) profile could represent these ITH is still an open question. We performed 181 multi-region tumor tissues sequencing and matched ctDNA sequencing from 32 operative NSCLC to compare ITH among different NSCLC subtypes, including EGFR-mutant lung adenocarcinoma (LUAD), KRAS-mutant LUAD, EGFR&KRAS-wild-type LUAD, and lung squamous cell carcinoma (LUSC), and examine potential value of ctDNA for ITH analysis. ITH is evaluated by ITH index (ITHi). If the somatic genetic alteration is shared by all the tissue regions, it is defined as trunk mutation. Otherwise, it is called branch mutation. The ITHi will be higher, if the tumor has less trunk mutations. We found EGFR-mutant LUAD showed significantly higher ITHi than KRAS-mutant LUAD/wild-type LUAD (P = 0.03) and numerically higher ITH than LUSC. For trunk mutations, driver mutations were identified at a higher proportion than passenger mutations (60% vs. 40%, P = 0.0023) in overall, especially in EGFR-mutant LUAD (86% vs. 14%, P = 0.0004), while it was opposite in KRAS-mutant LUAD (40% vs. 60%, P = 0.18). For branch mutations, the proportions of driver mutations and passenger mutations were similar for each NSCLC subtype. ctDNA analysis showed unsatisfactory detections of tumor-derived trunk and branch mutations (43% vs. 23%, P = 4.53e-6) among all NSCLC subtypes. In summary, EGFR-mutant LUAD has the highest ITH than other NSCLC subtypes, offering further understanding of tumorigenesis mechanisms among different NSCLC subtypes. Besides, ctDNA maybe not an appropriate method to reflect ITH.

Heterogeneity of Small Cell Lung Cancer Stem Cells

Small cell lung cancer, a subtype of lung cancer is an extremely malignant disease due to its metastases and recurrence. Patients with SCLC develop resistance to chemotherapy and the disease relapses. This relapse and resistance are attributed to the heterogeneity of SCLC. Various factors such as recurrent mutations in key regulatory genes such as TP53, RB1, and myc, epigenetic changes, and cancer stem cells contribute to the observed heterogeneity. Cancer stem cell models predict neuroendocrine origin of SCLC. Though an unambiguous established CSC marker has not been assigned, markers CD133, CD44 have been found associated with SCLC. Genetically engineered mouse models (GEMMs) allow the validation of driver mutations and are necessary for design of targeted therapy. This chapter outlines the factors contributing to SCLC heterogeneity, detection methods, and the current therapy trials.