Spatial distribution of EGFR and KRAS mutation frequencies correlates with histological growth patterns of lung adenocarcinomas

Crosstalk between tumor and microenvironment: Insights from spatial transcriptomics

Cancer is a dynamic disease, and clonal heterogeneity plays a fundamental role in tumor development, progression, and resistance to therapies. Single-cell and spatial multimodal technologies can provide a high-resolution molecular map of underlying genomic, epigenomic, and transcriptomic alterations involved in inter- and intra-tumor heterogeneity and interactions with the microenvironment. In this review, we provide a perspective on factors driving cancer heterogeneity, tumor evolution, and clonal states. We briefly describe spatial transcriptomic technologies and summarize recent literature that sheds light on the dynamical interactions between tumor states, cell-to-cell communication, and remodeling local microenvironment.

Molecular heterogeneity in histomorphologic subtypes of lung adeno carcinoma represents a challenge for treatment decision

Lung cancer is the leading cause in cancer related death, with non-small cell lung cancer (NSCLC) being the most frequent subtype. The importance of NSCLC is reflected by the various targeted therapy options especially for NSCLC adenocarcinomas (lung adeno carcinoma (LUAD)) as well as a set of options for immune therapies. However, despite these therapy advances, the majority of patients do not show a long-term response to either targeted therapy or immune checkpoint inhibition. One reason for treatment failure appears to be the NSCLC tumor heterogeneity. NSCLC heterogeneity might lead to an insufficient molecular characterization of a given sample due to the limited tumor material used for pathological assessment as the majority of analyses is performed on small biopsies. To get a more detailed insight into the tumor heterogeneity of NSCLC LUAD, especially in the light of its different histomorphological growth patterns, we analysed isolated NSCLC growth pattern areas and the corresponding entire tumor samples of a cohort of 31 NSLCS LUAD patients and compared their mutational landscape and their expression profiles. While significant differences of complex biomarkers, like tumor mutational burden (TMB) or microsatellite instability (MSI), were not detected between the five growth patterns -lepidic, papillary, micropapillary, acinar, and solid- we observed various subclonal mutations and copy number variants. Moreover, RNASeq analysis revealed growth pattern specific expression profiles affecting cellular processes like apoptosis, metastasis and proliferation. Taken together, our data provide novel insights into the tumor heterogeneity of LUAD required to overcome tumor heterogeneity related therapy resistance.

Spatial profiling of the microenvironment reveals low intratumoral heterogeneity and STK11-associated immune evasion in therapy-naïve lung adenocarcinomas

OBJECTIVE

Intratumoral heterogeneity was found to be a significant factor causing resistance to lung cancer therapies, including immune checkpoint blockade. Lesser is known about spatial heterogeneity of the tumor microenvironment (TME) and its association with genetic properties of the tumor, which is of particular interest in the therapy-naïve setting.

MATERIALS AND METHODS

We performed multi-region sampling (2-4 samples per tumor; total of 55 samples) from a cohort of 19 untreated stage IA-IIIB lung adenocarcinomas (n = 11 KRAS mutant, n = 1 ERBB2 mutant, n = 7 KRAS wildtype). For each sample the expression of 770 immunooncology-related genes was analyzed using the nCounter platform, while the mutational status was determined by hybrid capture-based next-generation sequencing (NGS) using a large panel covering more than 500 genes.

RESULTS

Global unsupervised analyses revealed clustering of the samples into two groups corresponding to a 'hot' or 'cold' immunologic tumor contexture based on the abundance of immune cell infiltrates. All analyzed specific immune cell signatures (ICsig) showed a significantly higher intertumoral than intratumoral heterogeneity (p < 0.02), as most of the analyzed cases (14/19) showed a very homogenous spatial immune cell profile. PD-L1 exhibited a significantly higher intertumoral than intratumoral heterogeneity (p = 1.03e-13). We found a specific association with 'cold' TME for STK11 (11/14, p < 0.07), but not KRAS, TP53, LRP1B, MTOR, U2AF1 co-mutations, and validated this finding using The Cancer Genome Atlas (TCGA) data.

CONCLUSION

Early-stage lung adenocarcinomas show considerable intertumoral, but limited intratumoral heterogeneity, which is clinically highly relevant as assessment before neoadjuvant treatment is based on small biopsies. STK11 mutations are specifically associated with a 'cold' TME, which could affect the efficacy of perioperative immunotherapy.

Association of frequent hypermethylation with high grade histological subtype in lung adenocarcinoma

Lung adenocarcinoma is classified morphologically into five histological subtypes according to the WHO classification. While each histological subtype correlates with a distinct prognosis, the molecular basis has not been fully elucidated. Here we conducted DNA methylation analysis of 30 lung adenocarcinoma cases annotated with the predominant histological subtypes and three normal lung cases using the Infinium BeadChip. Unsupervised hierarchical clustering analysis revealed three subgroups with different methylation levels: high-, intermediate-, and low-methylation epigenotypes (HME, IME, and LME). Micropapillary pattern (MPP)-predominant cases and those with MPP components were significantly enriched in HME (p = 0.02 and p = 0.03, respectively). HME cases showed a significantly poor prognosis for recurrence-free survival (p < 0.001) and overall survival (p = 0.006). We identified 365 HME marker genes specifically hypermethylated in HME cases with enrichment of "cell morphogenesis" related genes; 305 IME marker genes hypermethylated in HME and IME, but not in LME, with enrichment "embryonic organ morphogenesis"-related genes; 257 Common marker genes hypermethylated commonly in all cancer cases, with enrichment of "regionalization"-related genes. We extracted surrogate markers for each epigenotype and designed pyrosequencing primers for five HME markers (TCERG1L, CXCL12, FAM181B, HOXA11, GAD2), three IME markers (TBX18, ZNF154, NWD2) and three Common markers (SCT, GJD2, BARHL2). DNA methylation profiling using Infinium data was validated by pyrosequencing, and HME cases defined by pyrosequencing results also showed the worse recurrence-free survival. In conclusion, lung adenocarcinomas are stratified into subtypes with distinct DNA methylation levels, and the high-methylation subtype correlated with MPP-predominant cases and those with MPP components and showed a poor prognosis.

A computational modeling approach for predicting multicell spheroid patterns based on signaling-induced differential adhesion

Physiological and pathological processes including embryogenesis and tumorigenesis rely on the ability of individual cells to work collectively to form multicell patterns. In these heterogeneous multicell systems, cell-cell signaling induces differential adhesion between cells that leads to tissue-level patterning. However, the sensitivity of pattern formation to changes in the strengths of signaling or cell adhesion processes is not well understood. Prior work has explored these issues using synthetically engineered heterogeneous multicell spheroid systems, in which cell subpopulations engage in bidirectional intercellular signaling to regulate the expression of different cadherins. While engineered cell systems provide excellent experimental tools to observe pattern formation in cell populations, computational models of these systems may be leveraged to explore more systematically how specific combinations of signaling and adhesion parameters can drive the emergence of unique patterns. We developed and validated two- and three-dimensional agent-based models (ABMs) of spheroid patterning for previously described cells engineered with a bidirectional signaling circuit that regulates N- and P-cadherin expression. Systematic exploration of model predictions, some of which were experimentally validated, revealed how cell seeding parameters, the order of signaling events, probabilities of induced cadherin expression, and homotypic adhesion strengths affect pattern formation. Unsupervised clustering was also used to map combinations of signaling and adhesion parameters to these unique spheroid patterns predicted by the ABM. Finally, we demonstrated how the model may be deployed to design new synthetic cell signaling circuits based on a desired final multicell pattern.

Deciphering Tumour Heterogeneity: From Tissue to Liquid Biopsy

Simple Summary

Most malignant tumours are highly heterogeneous at molecular and phenotypic levels. Tumour variability poses challenges for the management of patients, as it arises between patients and even evolves in space and time within a single patient. Currently, treatment-decision making usually relies on the molecular characteristics of a limited tumour tissue sample at the time of diagnosis or disease progression but does not take into account the complexity of the bulk tumours and their constant evolution over time. In this review, we explore the extent of tumour heterogeneity and report the mechanisms that promote and sustain this diversity in cancers. We summarise the clinical strikes of tumour diversity in the management of patients with cancer. Finally, we discuss the current material and technological approaches that are relevant to adequately appreciate tumour heterogeneity.

Abstract

Human solid malignancies harbour a heterogeneous set of cells with distinct genotypes and phenotypes. This heterogeneity is installed at multiple levels. A biological diversity is commonly observed between tumours from different patients (inter-tumour heterogeneity) and cannot be fully captured by the current consensus molecular classifications for specific cancers. To extend the complexity in cancer, there are substantial differences from cell to cell within an individual tumour (intra-tumour heterogeneity, ITH) and the features of cancer cells evolve in space and time. Currently, treatment-decision making usually relies on the molecular characteristics of a limited tumour tissue sample at the time of diagnosis or disease progression but does not take into account the complexity of the bulk tumours and their constant evolution over time. In this review, we explore the extent of tumour heterogeneity with an emphasis on ITH and report the mechanisms that promote and sustain this diversity in cancers. We summarise the clinical strikes of ITH in the management of patients with cancer. Finally, we discuss the current material and technological approaches that are relevant to adequately appreciate ITH.

Fusion-positive non-small cell lung carcinoma: Biological principles, clinical practice, and diagnostic implications

Based on superior efficacy and tolerability, targeted therapy is currently preferred over chemotherapy and/or immunotherapy for actionable gene fusions that occur in late-stage non-small cell lung carcinoma (NSCLC). Consequently, current clinical practice guidelines mandate testing for ALK, ROS1, NTRK, and RET gene fusions in all patients with newly diagnosed advanced non-squamous NSCLC (NS-NSCLC). Gene fusions can be detected using different approaches, but today RNA next-generation sequencing (NGS) or combined DNA/RNA NGS is the method of choice. The discovery of other gene fusions (involving, eg, NRG1, NUT, FGFR1, FGFR2, MET, BRAF, EGFR, SMARC fusions) and their partners has increased progressively in recent years, leading to the development of new and promising therapies and mandating the development and implementation of comprehensive detection methods. The purpose of this review is to focus on recent data concerning the main gene fusions identified in NSCLC, followed by the discussion of major challenges in this domain.

The role of molecular heterogeneity targeting resistance mechanisms to lung cancer therapies

Introduction: The treatment scenario of lung cancer is rapidly evolving through time. In parallel, growing evidence is accumulating on different mechanisms of treatment resistance. Inter- and intra-tumor heterogeneity define the spatial and temporal tumor clonal evolution, that is at the basis of tumor progression and resistance to anticancer treatments.Areas covered: This review summarizes the available evidence on molecular heterogeneity in lung cancer, from diagnosis to the occurrence of treatment resistance. The application of novel molecular diagnostic methods to detect molecular heterogeneity, and the implications of understanding heterogeneity for drug development strategies are discussed, with focus on clinical relevance and impact on patients' survival.Expert opinion: The current knowledge of molecular heterogeneity allows to identify different molecular subgroups of patients within the same conventional tumor type. Deeper understanding of heterogeneity determinants and the possibility to comprehensively investigate tumor molecular patterns will lead to the development of personalized treatment approaches, with the final goal to overcome resistance and prolong survival in lung cancer patients.

The evolving landscape of biomarker testing for non-small cell lung cancer in Europe

The discovery of oncogenic driver mutations rendering non-small cell lung cancer (NSCLC) targetable by small-molecule inhibitors, and the development of immunotherapies, have revolutionised NSCLC treatment. Today, instead of non-selective chemotherapies, all patients with advanced NSCLC eligible for treatment (and increasing numbers with earlier, less extensive disease) require fast and comprehensive screening of biomarkers for first-line patient selection for targeted therapy, chemotherapy, or immunotherapy (with or without chemotherapy). To avoid unnecessary re-biopsies, biomarker screening before first-line treatment should also include markers that are actionable from second-line onwards; PD-L1 expression testing is also mandatory before initiating treatment. Population differences exist in the frequency of oncogenic driver mutations: EGFR mutations are more frequent in Asia than Europe, whereas the converse is true for KRAS mutations. In addition to approved first-line therapies, a number of emerging therapies are being investigated in clinical trials. Guidelines for biomarker testing vary by country, with the number of actionable targets and the requirement for extensive molecular screening strategies expected to increase. To meet diagnostic demands, rapid screening technologies for single-driver mutations have been implemented. Improvements in DNA- and RNA-based next-generation sequencing technologies enable analysis of a group of genes in one assay; however, turnaround times remain relatively long. Consequently, rapid screening technologies are being implemented alongside next-generation sequencing. Further challenges in the evolving landscape of biomarker testing in NSCLC are actionable primary and secondary resistance mechanisms to targeted therapies. Therefore, comprehensive testing on re-biopsies, collected at the time of disease progression, in combination with testing of circulating tumour DNA may provide important information to guide second- or third-line therapies. Furthermore, longitudinal biomarker testing can provide insights into tumour evolution and heterogeneity during the course of the disease. We summarise best practice strategies for Europe in the changing landscape of biomarker testing at diagnosis and during treatment.

Understanding EGFR heterogeneity in lung cancer

The advances in understanding the inherited biological mechanisms of non-small cell lung cancer harbouring epidermal growth factor receptor (EGFR) mutations led to a significant improvement in the outcomes of patients treated with EGFR tyrosine kinase inhibitors. Despite these clinically impressive results, clinical results are not always uniform, suggesting the need for deepening the molecular heterogeneity of this molecularly defined subgroup of patients beyond the clinical and biological surface.The availability of tissue and blood-based tumour genotyping allows us to improve the understanding of molecular and genetic intratumor heterogeneity, driving the measurement of clonal evaluation in patients with lung cancer carrying EGFR mutations. Genetic diversification, clonal expansion and selection are highly variable patterns of genetic diversity, resulting in different biological entities, also a prerequisite for Darwinian selection and therapeutic failure.Such emerging pieces of evidence on the genetic diversity, including adaptive and immunomodulated aspects, provide further evidence for the role of the tumour microenvironment (TME) in drug-resistance and immune-mediated mechanisms. Matching in daily clinical practice, the detailed genomic profile of lung cancer disease and tracking the clonal evolution could be the way to individualise the further target treatments in EGFR-positive disease. Characterising the tumour and immune microenvironment during the time of the cancer evaluation could be the way forward for the qualitative leap needed from bench to bedside. Such a daring approach, aiming at personalising treatment selection in order to exploit the TME properties and weaken tumour adaptivity, should be integrated into clinical trial design to optimise patient outcome.

Approaching sites of action of drugs in clinical pharmacology: New analytical options and their challenges

Clinical pharmacology is an important discipline for drug development aiming to define pharmacokinetics (PK), pharmacodynamics (PD) and optimum exposure to drugs, i.e. the concentration-response relationship and its modulators. For this purpose, information on drug concentrations at the anatomical, cellular and molecular sites of action is particularly valuable. In pharmacological assays, the limited accessibility of target cells in readily available samples (i.e. blood) often hampers mass spectrometry-based monitoring of the absolute quantity of a compound and the determination of its molecular action at the cellular level. Recently, new sample collection methods have been developed for the specific capture of rare circulating cells, especially for the diagnosis of circulating tumour cells. In parallel, new advances and developments in mass spectrometric instrumentation now allow analyses to be scaled down to the cellular level. Together, these developments may permit the monitoring of minute drug quantities and show their effect at the cellular level. In turn, such PK/PD associations on a cellular level would not only enrich our pharmacological knowledge of a given compound but also expand the basis for PK/PD simulations. In this review, we describe novel concepts supporting clinical pharmacology at the anatomical, cellular and molecular sites of action, and highlight the new challenges in mass spectrometry-based monitoring. Moreover, we present methods to tackle these challenges and define future needs.

Long noncoding RNA TP53TG1 promotes pancreatic ductal adenocarcinoma development by acting as a molecular sponge of microRNA-96

Long noncoding RNAs (lncRNAs) are emerging as key regulators in cancer initiation and progression. TP53TG1 is a recently identified lncRNA and several studies have shown that TP53TG1 may play the role of tumor suppressor gene or oncogene in different tumors. Nevertheless, the involvement of TP53TG1 in carcinogenesis of pancreatic ductal adenocarcinoma (PDAC) has not been characterized. In our studies, we identified that TP53TG1 was highly expressed in PDAC and was a novel regulator of PDAC development. Knockdown of TP53TG1 inhibited proliferation, induced apoptosis, and decreased migration and invasion in PDAC cells, whereas enhanced expression of TP53TG1 had the opposite effects. Mechanistically, TP53TG1 could directly bind to microRNA (miR)-96 and effectively function as a sponge for miR-96, thus antagonizing the functions of miR-96 and leading to derepression of its endogenous target KRAS, which is a core oncogene in the initiation and maintenance of PDAC. Taken together, these observations imply that TP53TG1 contributes to the growth and progression of PDAC by acting as a competing endogenous RNA (ceRNA) to competitively bind to miR-96 and regulate KRAS expression, which highlights the importance of the complicated miRNA-lncRNA network in modulating the progression of PDAC.

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.

Molecular heterogeneity in lung cancer: from mechanisms of origin to clinical implications

Molecular heterogeneity is a frequent event in cancer responsible of several critical issues in diagnosis and treatment of oncologic patients. Lung tumours are characterized by high degree of molecular heterogeneity associated to different mechanisms of origin including genetic, epigenetic and non-genetic source. In this review, we provide an overview of recognized mechanisms underlying molecular heterogeneity in lung cancer, including epigenetic mechanisms, mutant allele specific imbalance, genomic instability, chromosomal aberrations, tumor mutational burden, somatic mutations. We focus on the role of spatial and temporal molecular heterogeneity involved in therapeutic implications in lung cancer patients.

Subclonal evolution of pulmonary adenocarcinomas delineated by spatially distributed somatic mitochondrial mutations

OBJECTIVES

The potential role of cancer associated somatic mutations of the mitochondrial genome (mtDNA) is controversial and still poorly understood. Our group and others recently challenged a direct tumorigenic impact and suggested a passenger-like character. In combination with the known increased mutation rate, somatic mtDNA mutations account for an interesting tool to delineate tumor evolution. Here, we comprehensively analyzed the spatial distribution of somatic mtDNA mutations throughout whole tumor sections of pulmonary adenocarcinoma (ADC).

MATERIALS AND METHODS

Central sections of 19 ADC were analyzed in a segmented manner (11-34 segments/tumor) together with non-neoplastic tissue samples and lymph node metastasis, if present. We performed whole mtDNA sequencing and real-time PCR based quantification of mtDNA copy numbers for all samples. Further, histological growth patterns were determined on H&E sections and the tumor cell content was quantified by digital pathology analyses.

RESULTS

Somatic mtDNA mutations were present in 96% (18/19) of the analyzed tumors, either ubiquitously or restricted to specific tumor regions. Spatial and histological mapping of the mutations enabled the identification of subclonal structures and phylogenetic relations within a tumor section indicating different progression levels. In this regard, lymph node metastases seem to be related to early events in ADC development. There was no concurrence between histological and mtDNA mutation based clusters. However, micropapillary patterns occurred only in tumors with ubiquitous mutations. ADC with more than two ubiquitous mutations were associated with shorter disease-free survival (p < 0.01).

CONCLUSION

Cancer related mtDNA mutations are interesting candidates for the understanding of subclonal ADC evolution and perspectively for monitoring tumor progression. Our data reveal a potential prognostic relevance of somatic mtDNA mutations.

Overview on Clinical Relevance of Intra-Tumor Heterogeneity

Today, clinical evaluation of tumor heterogeneity is an emergent issue to improve clinical oncology. In particular, intra-tumor heterogeneity (ITH) is closely related to cancer progression, resistance to therapy, and recurrences. It is interconnected with complex molecular mechanisms including spatial and temporal phenomena, which are often peculiar for every single patient. This review tries to describe all the types of ITH including morphohistological ITH, and at the molecular level clonal ITH derived from genomic instability and nonclonal ITH derived from microenvironment interaction. It is important to consider the different types of ITH as a whole for any patient to investigate on cancer progression, prognosis, and treatment opportunities. From a practical point of view, analytical methods that are widely accessible today, or will be in the near future, are evaluated to investigate the complex pattern of ITH in a reproducible way for a clinical application.