Intertumoral Heterogeneity Research Articles

Integrated genomic analysis reveals actionable targets in pediatric spinal cord low-grade gliomas

Gliomas are the most common central nervous tumors in children and adolescents. However, spinal cord low-grade gliomas (sLGGs) are rare, with scarce information on tumor genomics and epigenomics. To define the molecular landscape of sLGGs, we integrated clinical data, histology, and multi-level genetic and epigenetic analyses on a consecutive cohort of 26 pediatric patients. Driver molecular alteration was found in 92% of patients (24/26). A novel variant of KIAA1549:BRAF fusion (ex10:ex9) was identified using RNA-seq in four cases. Importantly, only one-third of oncogenic drivers could be revealed using standard diagnostic methods, and two-thirds of pediatric patients with sLGGs required extensive molecular examination. The majority (23/24) of detected alterations were potentially druggable targets. Four patients in our cohort received targeted therapy with MEK or NTRK inhibitors. Three of those exhibited clinical improvement (two with trametinib, one with larotrectinib), and two patients achieved partial response. Methylation profiling was implemented to further refine the diagnosis and revealed intertumoral heterogeneity in sLGGs. Although 55% of tumors clustered with pilocytic astrocytoma, other rare entities were identified in this patient population. In particular, diffuse leptomeningeal glioneuronal tumors (n = 3) and high-grade astrocytoma with piloid features (n = 1) and pleomorphic xanthoastrocytoma (n = 1) were present. A proportion of tumors (14%) had no match with the current version of the classifier. Complex molecular genetic sLGGs characterization was invaluable to refine diagnosis, which has proven to be essential in such a rare tumor entity. Moreover, identifying a high proportion of drugable targets in sLGGs opened an opportunity for new treatment modalities.

245. CLINICAL UTILITY OF CTDNA IN LONGITUDINAL MONITORING OF TREATMENT RESPONSES AND RELAPSE IN METASTATIC ESOPHAGEAL SQUAMOUS CELL CARCINOMA

Abstract Esophageal squamous cell carcinoma (ESCC) is a deadly cancer frequently diagnosed only at advanced stages, contributing to high mortality. In this study, circulating tumor DNA (ctDNA), which is DNA shed from the tumor into the bloodstream, was utilized for real-time monitoring of treatment response and early detection of relapse using next-generation sequencing. The clinical utility of ctDNA as a biomarker for monitoring disease burden and treatment response was evaluated. A total of 72 metastatic ESCC patients, who received palliative chemotherapy, were recruited. Blood was collected from the patients before, during, and at the end of treatment. ctDNA was extracted from plasma and the mutation profiles were determined by targeted-capture sequencing using the Roche AVENIO ctDNA expanded 77-genes kit. Mutations or amplification detected in the ctDNA were validated by Sanger sequencing or digital PCR. Mutations in the tumors were validated using formalin-fixed paraffin-embedded (FFPE) tissue with the Roche AVENIO Tumor tissue expanded 77-genes kit. Single nucleotide variations (SNVs) were detected in 92% and copy number variations (CNVs) were detected in 22% of the metastatic ESCC patients. The most frequently mutated genes were TP53, NFE2L2 and PIK3CA. The presence of TP53 mutations at pre-cycle III treatment was associated with poor progression-free survival and overall survival. Longitudinal ctDNA analysis showed good concordance between mutant allele frequency (MAF) and tumor burden and the change in MAF preceded the radiographic relapse with an average of 46 days. ctDNA also demonstrated the ability to capture inter-tumor heterogeneity in the primary tumor and lymph node metastasis. Using the 77-gene panel, mutations were detected in ctDNA of metastatic ESCC patients; the change in MAF reflected the tumor burden. Serial analysis of ctDNAs indicates the usefulness of ctDNA as a prognostic and predictive biomarker for real-time non-invasive monitoring to assess tumor burden and to predict treatment efficacy, disease relapse, and patient survival. Mutation profiles in ctDNA may also be useful in guiding personal targeted therapy.

Bioimaging Nucleic-Acid Aptamers with Different Specificities in Human Glioblastoma Tissues Highlights Tumoral Heterogeneity.

Nucleic-acid aptamers are of strong interest for diagnosis and therapy. Compared with antibodies, they are smaller, stable upon variations in temperature, easy to modify, and have higher tissue-penetration abilities. However, they have been little described as detection probes in histology studies of human tissue sections. In this study, we performed fluorescence imaging with two aptamers targeting cell-surface receptors EGFR and integrin α5β1, both involved in the aggressiveness of glioblastoma. The aptamers’ cell-binding specificities were confirmed using confocal imaging. The affinities of aptamers for glioblastoma cells expressing these receptors were in the 100–300 nM range. The two aptamers were then used to detect EGFR and integrin α5β1 in human glioblastoma tissues and compared with antibody labeling. Our aptafluorescence assays proved to be able to very easily reveal, in a one-step process, not only inter-tumoral glioblastoma heterogeneity (differences observed at the population level) but also intra-tumoral heterogeneity (differences among cells within individual tumors) when aptamers with different specificities were used simultaneously in multiplexing labeling experiments. The discussion also addresses the strengths and limitations of nucleic-acid aptamers for biomarker detection in histology.

Quantitative Spatial Profiling of Immune Populations in Pancreatic Ductal Adenocarcinoma Reveals Tumor Microenvironment Heterogeneity and Prognostic Biomarkers.

Quantitative image analysis of PDAC specimens reveals intertumoral and intratumoral heterogeneity of immune populations and identifies spatial immune architectures that are significantly associated with disease prognosis.

Abstract B020: Multimodal single-cell analyses reveal identification of unique transcriptional subgroups in ewing sarcoma

Abstract Ewing sarcoma (EwS) tumors are driven by pathognomonic fusions between FET proteins and ETS family transcription factors (most frequently EWS::FLI1). EWS::FLI1 drives tumorigenesis through massive transcriptomic and epigenomic rewiring. Despite mutational homogeneity, EwS are highly transcriptionally heterogeneous suggesting that cell context is a key determinant of EWS::FLI1-driven gene signatures. Fusion protein activity has been revealed as a core source of EwS heterogeneity. However, deep investigation into the transcriptomic and epigenomic heterogeneity of EwS cells has yet to be described. Molecular subtyping of EwS has thus far proven to be difficult to achieve with bulk RNA-sequencing approaches. We hypothesized that single-cell characterization of EwS cells would provide the necessary resolution to allow identification and characterization of transcriptionally distinct tumor subgroups. We subjected eight established EwS cell lines, one PDX-derived EwS line, and five non-EwS cell lines to single-cell multiomic (ATAC + RNA) sequencing. A range of 1300-3800 live cells were captured per sample, with an average of 25,000 transcript and accessible reads per cell. Initial analysis of transcriptomes confirmed the EwS-specific, EWS::FLI1-dependent signature gene sets in EwS samples. Integrated analysis of the multiome data from the 9 EwS samples identified inter-tumor heterogeneity and unsupervised k-means clustering revealed three molecular subgroups that were not evident from expression data alone. Subgroup 1 comprised only the A673 cell line, while the remaining 8 EwS samples were split between subgroups 2 and 3. Gene ontology analysis defined enrichment of distinct gene sets across the 3 subgroups. Interestingly, expression of subgroup 2-defining genes was reduced following knockdown of EWSR1::FLI1, while expression of subgroup 3-defining genes increased. Thus, these data show that transcriptionally distinct subgroups of EwS exist and these are defined, in part, by whether EWS::FLI1-dependent gene activation or gene repression dominates transcriptional rewiring. Our ongoing studies suggest that these molecular subgroups are defined by cooperation between the fusion and cell context-dependent transcription factors. Future analyses will determine if these distinct multiomic programs exist in primary patients tumors and test the pathobiologic and clinical significance of these novel molecular subgroups. Citation Format: April A. Apfelbaum, Olivia Waltner, Shruti S. Bhise, Sami Kanaan, Jay F. Sarthy, Scott N. Furlan, Elizabeth R. Lawlor. Multimodal single-cell analyses reveal identification of unique transcriptional subgroups in ewing sarcoma [abstract]. In: Proceedings of the AACR Special Conference: Sarcomas; 2022 May 9-12; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2022;28(18_Suppl):Abstract nr B020.

Genetic and microenvironmental intra-tumor heterogeneity impacts colorectal cancer evolution and metastatic development

Colorectal cancer (CRC) is a highly diverse disease, where different genomic instability pathways shape genetic clonal diversity and tumor microenvironment. Although intra-tumor heterogeneity has been characterized in primary tumors, its origin and consequences in CRC outcome is not fully understood. Therefore, we assessed intra- and inter-tumor heterogeneity of a prospective cohort of 136 CRC samples. We demonstrate that CRC diversity is forged by asynchronous forms of molecular alterations, where mutational and chromosomal instability collectively boost CRC genetic and microenvironment intra-tumor heterogeneity. We were able to depict predictor signatures of cancer-related genes that can foresee heterogeneity levels across the different tumor consensus molecular subtypes (CMS) and primary tumor location. Finally, we show that high genetic and microenvironment heterogeneity are associated with lower metastatic potential, whereas late-emerging copy number variations favor metastasis development and polyclonal seeding. This study provides an exhaustive portrait of the interplay between genetic and microenvironment intra-tumor heterogeneity across CMS subtypes, depicting molecular events with predictive value of CRC progression and metastasis development.

KS05.7.A Characterization of the immune composition of extreme long-term survivors with malignant glioma at single-cell level

Abstract Background Glioblastoma Multiforme (GBM) remains the most common malignant primary brain tumor with a dismal prognosis that rarely exceeds beyond two years despite extensive therapy, which consists of maximal safe surgical resection, radiotherapy and/or chemotherapy. Recently, it has become clear that GBM is not one homogeneous entity and that both intra-and intertumoral heterogeneity contribute significantly to differences in tumoral behavior which may consequently be responsible for differences in survival. Strikingly and in spite of its dismal prognosis, small fractions of GBM patients seem to display extended survival compared to the large majority of patients. The underlying mechanisms for this peculiarity remain largely unknown however, even though emerging data suggest that both cancer cell-autonomous and microenvironmental factors and their interplay probably play an important role. Material and Methods We used high-dimensional, multiplexed immunohistochemistry to spatially, and cytometry by time-of-flight to quantitively characterize the cell constitution and interactions within the tumor microenvironment (TME) in 21 extreme long-term survivors (living over ten years since primary diagnosis or five years after recurrence) and 42 deeply matched short-term controls (living under 1.5 year) on a single cell level. For all tumors (epi-)genetic data was also collected. Results We identified a high level of both inter-and intrapatient heterogeneity defined by several distinct tumor niches, as well as described interactions within these niches and with the surrounding infiltrating immune cells of the TME. By linking patient characteristics with the heterogeneous immune composition we are building an immune stratification that can be linked to patient survival in GBM. Conclusion Generating an immune stratification for GBM will allow us to identify immune characteristics responsible for longer or even exceptional survival, as well as thoroughly identify tumor components that may serve as a potential target for personalized treatment strategies. Therefore, this study is also an essential initial step towards such clinical trials which alter the TME in a favorable way with a personalized modulation strategy.

MA05.07 Intertumoral Molecular Heterogeneity of Non-small Cell Lung Cancer with MET Exon 14 Skipping

MET exon 14 skipping, as a rare driver for non-small cell lung cancer (NSCLC), can be successfully targeted by MET specific tyrosine kinase inhibitors (TKI) like Savolitinib, Tepotinib, and Capmatinib. Recent clinical trials of MET selective TKIs displayed encouraging clinical efficacy. While nearly half of NSCLC patients with MET exon 14 skipping did not benefit from MET-TKI treatment, which indicated biological heterogeneity in NSCLCs driven by METex14 skipping. This study aims to disclose the intertumoral heterogeneity of METex14 skipping positive NSCLCs at the functional level.

P2.10-04 Immunologic Subtype of Small Cell Lung Carcinoma Dictates Susceptibility to NK Cell-Mediated Cytotoxicity

Small cell lung carcinoma (SCLC) comprises approximately 15% of all lung cancer cases and SCLC patients initially respond to cytotoxic chemotherapy, but resistance inevitably emerges. Despite recent incorporation of immune checkpoint blockade (ICB) into first line treatment, predictive biomarkers of response remain lacking and patients with SCLC continue to have a poor prognosis with limited treatment options. Notably, recent transcriptomic profiling of SCLC cell lines and patient samples has indicated significant inter-tumoral and intra-tumoral heterogeneity.

Single-cell phenotypic profiling to identify a set of immune cell protein biomarkers for relapsed and refractory diffuse large B cell lymphoma: A single-center study.

Diffuse large B-cell lymphoma (DLBCL) is the most common invasive type of non-Hodgkin lymphoma. Cell-of-origin (COO) classification is related to patients' prognoses. Primary drug resistance in treatment for DLBCL has been observed. The specific serum biomarkers in these patients who suffer from relapsed and refractory (R/R)-DLBCL remains unclear. In the current study, using single-cell RNA sequencing (scRNA-seq) and mass cytometry (CyTOF), we determined and verified immune cell biomarkers at the mRNA and protein levels in single-cell resolution from 18 diagnostic PBMC specimens collected from patients with R/R DLBCL. As controls, 5 PBMC specimens from healthy volunteers were obtained. We identified a panel of 35 surface marker genes for the features of R/R DLBCL unique cell cluster by scRNA-seq of 8 R/R DLBCL patient samples and validated its efficiency in an external cohort consisting of 10 R/R DLBCL patients by CyTOF. The cell clustering and dimension reduction were compared among R/R DLBCL samples in CyTOF Space with COO as well as the C-MYC expression designation. Immune cells from each patient occupied unique regions in the 32-dimensional phenotypic space with no apparent clustering of samples into discrete subtypes. Significant heterogeneity observed in subgroups was mainly attributed to individual differences among samples and not to expression differences in a single, homogeneous immune cell subpopulation. The marker panel showed reliability in labeling R/R DLBCL without any influence from COO stratification and C-MYC expression designation. Furthermore, we compared all the markers between R/R DLBCL and normal samples. A total of 12 biomarkers were significantly overexpressed in R/R DLBCL relative to the normal samples. Therefore, we further optimized the diagnostic biomarker panel of R/R DLBCL comprising CD82, CD55, CD36, CD63, CD59, IKZF1, CD69, CD163, CD14, CD226, CD84, and CD31. In summary, we developed a novel set of biomarkers for the diagnoses of patients with R/R DLBCL. Detections procedures at single-cell resolution provide precise biomarkers, which may substantially overcome intertumoral and intratumoral heterogeneity among primary samples. The findings confirmed that each case was unique and may comprise multiple, genetically distinct subclones.

Machine learning algorithm-generated and multi-center validated melanoma prognostic signature with inspiration for treatment management.

Although immunotherapy and targeted treatments have dramatically improved the survival of melanoma patients, the intra- or intertumoral heterogeneity and drug resistance have hindered the further expansion of clinical benefits. The 96 combination frames constructed by ten machine learning algorithms identified a prognostic consensus signature based on 1002 melanoma samples from nine independent cohorts. Clinical features and 26 published signatures were employed to compare the predictive performance of our model. A machine learning-based prognostic signature (MLPS) with the highest average C-index was developed via 96 algorithm combinations. The MLPS has a stable and excellent predictive performance for overall survival, superior to common clinical traits and 26 collected signatures. The low MLPS group with a better prognosis had significantly enriched immune-related pathways, tending to be an immune-hot phenotype and possessing potential immunotherapeutic responses to anti-PD-1, anti-CTLA-4, and MAGE-A3. On the contrary, the high MLPS group with more complex genomic alterations and poorer prognoses is more sensitive to the BRAF inhibitor dabrafenib, confirmed in patients with BRAF mutations. MLPS could independently and stably predict the prognosis of melanoma, considered a promising biomarker to identify patients suitable for immunotherapy and those with BRAF mutations who would benefit from dabrafenib.

Improving on-treatment risk stratification of cancer patients with refined response classification and integration of circulating tumor DNA kinetics

BackgroundSignificant intertumoral heterogeneity exists as antitumor treatment is introduced. Heterogeneous therapeutic responses are conventionally evaluated by imaging examinations based on Response Evaluation Criteria in Solid Tumors (RECIST); nevertheless, there are increasing recognitions that they do not fully capture patient clinical benefits. Currently, there is a paucity of data regarding the clinical implication of biological responses assessed by liquid biopsy of on-treatment circulating tumor DNA (ctDNA). Here, we investigated whether biological response evaluated by ctDNA kinetics added critical information to the RECIST, and whether integrating on-treatment biological response information refined risk stratification of cancer patients.MethodsIn this population-based cohort study, we included 821 patients with Epstein-Barr virus (EBV)-associated nasopharynx of head and neck cancer (NPC) receiving sequential neoadjuvant chemotherapy (NAC) and chemoradiotherapy (CRT), who had pretreatment and on-treatment cfEBV DNA and magnetic resonance imaging (MRI) surveillance. Biological responses evaluated by cfEBV DNA were profiled and compared with conventional MRI-based RECIST evaluation. The inverse probability weighting (IPW)-adjusted survival analysis was performed for major survival endpoints. The Cox proportional hazard regression [CpH]-based model was developed to predict the on-treatment ctDNA-based individualized survival.ResultsOf 821 patients, 71.4% achieved complete biological response (cBR) upon NAC completion. RECIST-based response evaluations had 25.3% discordance with ctDNA-based evaluations. IPW-adjusted survival analysis revealed that cfEBV DNApost-NAC was a preferential prognosticator for all endpoints, especially for distant metastasis. In contrast, radiological response was more preferentially associated with locoregional recurrence. Intriguingly, cfEBV DNApost-NAC further stratified RECIST-responsive and non-responsive patients; RECIST-based non-responsive patients with cBR still derived substantial clinical benefits. Moreover, detectable cfEBV DNApost-NAC had 83.6% prediction sensitivity for detectable post-treatment ctDNA, which conferred early determination of treatment benefits. Finally, we established individualized risk prediction models and demonstrated that introducing on-treatment ctDNA significantly refined risk stratification.ConclusionsOur study helps advance the implementation of ctDNA-based testing in therapeutic response evaluation for a refined risk stratification. The dynamic and refined risk profiling would tailor future liquid biopsy-based risk-adapted personalized therapy.

Biomarkers in Anal Cancer: Current Status in Diagnosis, Disease Progression and Therapeutic Strategies.

Squamous cell carcinoma of the anal canal (SCCA) is a rare neoplasm, but with rising incidence rates in the past few decades; it is etiologically linked with the human papillomavirus (HPV) infection and is especially prevalent in immunocompromised patients, mainly those infected with HIV. Fluoropyrimidine-based chemoradiotherapy remains the cornerstone of the treatment of non-metastatic disease, but the locally advanced disease still presents high rates of disease recurrence and systemic therapy of SCCA is an unmet clinical need. Despite sharing common molecular aspects with other HPV-related malignancies, such as cervical and head and neck cancers, SCCA presents specific epigenomic, genomic, and transcriptomic abnormalities, which suggest that genome-guided personalized therapies should be specifically designed for this disease. Actionable mutations are rare in SCCA and immune checkpoint inhibition has not yet been proven useful in an unselected population of patients. Therefore, advances in systemic therapy of SCCA will only be possible with the identification of predictive biomarkers and the subsequent development of targeted therapies or immunotherapeutic approaches that consider the unique tumor microenvironment and the intra- and inter-tumoral heterogeneity. In the present review, we address the molecular characterization of SCCA and discuss potential diagnostic, predictive and prognostic biomarkers of this complex and challenging disease.

Temporal Heterogeneity of HER2 Expression and Spatial Heterogeneity of 18F-FDG Uptake Predicts Treatment Outcome of Pyrotinib in Patients with HER2-Positive Metastatic Breast Cancer.

Simple SummaryTumor heterogeneity plays an important role in malignant behaviors and treatment responses. This study aimed to evaluate the temporal and spatial heterogeneity in clinical practice and investigate its impact on the treatment outcome of pyrotinib in patients with HER2-positive metastatic breast cancer. Temporal heterogeneity was evaluated by the discordance between primary and metastatic immunohistochemistry results. 18F-FDG uptake heterogeneity on baseline PET/CT scan was assessed to reflect spatial tumor heterogeneity among metastases. Our results showed that heterogeneous HER2 status between primary and metastatic lesions and spatial 18F-FDG uptake heterogeneity were predictive of poorer outcomes of pyrotinib treatment. The best method to evaluate tumor heterogeneity in clinical practice still needs to be identified. Temporal heterogeneity of HER2 expression and spatial heterogeneity of 18F-FDG uptake provided practically applicable methods to assess tumor heterogeneity and potential guidance for treatment decisions.Background: This study aimed to evaluate tumor heterogeneity of metastatic breast cancer (MBC) and investigate its impact on the efficacy of pyrotinib in patients with HER2-positive MBC. Methods: MBC patients who underwent 18F-FDG PET/CT before pyrotinib treatment were included. Temporal and spatial tumor heterogeneity was evaluated by the discordance between primary and metastatic immunohistochemistry (IHC) results and baseline 18F-FDG uptake heterogeneity (intertumoral and intratumoral heterogeneity indexes: HI-inter and HI-intra), respectively. Progression-free survival (PFS) was estimated by the Kaplan–Meier method and compared by a log-rank test. Results: A total of 572 patients were screened and 51 patients were included. In 36 patients with matched IHC results, 25% of them had HER2 status conversion. Patients with homogenous HER2 positivity had the longest PFS, followed by patients with gained HER2 positivity, while patients with HER2 negative conversion could not benefit from pyrotinib (16.8 vs. 13.7 vs. 3.6 months, p < 0.0001). In terms of spatial heterogeneity, patients with high HI-intra and HI-inter had significantly worse PFS compared to those with low heterogeneity (10.6 vs. 25.3 months, p = 0.023; 11.2 vs. 25.3 months, p = 0.040). Conclusions: Temporal heterogeneity of HER2 status and spatial heterogeneity of 18F-FDG uptake could predict the treatment outcome of pyrotinib in patients with HER2-positive MBC, which provide practically applicable methods to assess tumor heterogeneity and guidance for treatment decisions.

Frequency and Prognostic Significance of Intertumoural Heterogeneity in Multifocal Jejunoileal Neuroendocrine Tumours.

Simple SummaryWell differentiated jejunoileal neuroendocrine tumors (SI-NETs) commonly present as multiple primaries, which are believed to be clonally unrelated. Our study aimed to explore whether these multifocal lesions show intertumoral differences between the most common histomorphological parameters and if so, whether these differences can be associated with patient prognosis. While WHO grade and standard neuroendocrine markers were found to be mostly stable, we observed intertumoral heterogeneity in the expression of SSTR2, CDX2, and serotonin, but observed no survival differences between the expression groups or in comparison to unifocal NETs. Although multifocal SI-NETs showed some degree of heterogeneity in their central morphological parameters, these findings do not appear to be of major clinical significance, rendering an extensive testing of all multifocal lesions as not necessarily required.Background: A recent study found that multifocal jejunoileal neuroendocrine tumors (SI-NETs) are genetically unrelated synchronous neoplasms. So far, it is unclear if this finding of synchronous independent neoplasms is mirrored by heterogeneity of key morphological parameters of SI-NETs and how it affects patient survival. Methods: We separately assessed WHO grade (based on the Ki-67 index), expression of basal diagnostic markers (synaptophysin/chromogranin A/CDX2/serotonin), SSTR2a, and the contexture of the immunogenic microenvironment in 146 separate tumors from 28 patients with multifocal SI-NETs and correlated the results with clinicopathological factors and survival. Results: Synaptophysin and chromogranin A were strongly expressed in all tumors. WHO grade was concordant within all multifocal lesions in more than 80% of cases and the highest grade was usually found in the most advanced primary. Intertumoral expression of serotonin, SSTR2, and CDX2 was discrepant in 32%, 43%, and 50% of all patients, respectively. Neither heterogeneity of any of the aforementioned markers nor multifocality itself had any impact on patient survival (p = n.s.). Discussion: Multifocal SI-NET show considerable variability in some of the central diagnostic parameters. However, neither intertumoral heterogeneity of those parameters nor multifocality itself had any impact on patient survival, showing that extensive testing of all multifocal lesions is not necessarily required.

Predictive Biomarkers of Response to Neoadjuvant Chemotherapy in Breast Cancer: Current and Future Perspectives for Precision Medicine.

Simple SummaryDespite the increased use of neoadjuvant chemotherapy in the early setting of breast cancer, there is a clinical need for predictive markers of response in daily practice. In the era of precision medicine and personalized treatment, new predictive markers that enable the better selection of patients for specific therapies are required. In this review, we describe the current knowledge about the molecular biomarkers used for clinical decision making for patients with breast cancer. We also report how microenvironment-driven intratumoral heterogeneity may influence the validation of biomarkers useful for precision medicine. We provide an overview of promising biomarkers, including pathological markers, genetic signatures, radiological techniques and liquid biopsies, with a great potential to be implemented in routine clinical practice. Finally, we discuss the use of relevant pre-clinical models of breast cancer to integrate microenvironmental specificities in order to identify and validate reliable biomarkers of (non-)response to neoadjuvant chemotherapy.Pathological complete response (pCR) after neoadjuvant chemotherapy in patients with early breast cancer is correlated with better survival. Meanwhile, an expanding arsenal of post-neoadjuvant treatment strategies have proven beneficial in the absence of pCR, leading to an increased use of neoadjuvant systemic therapy in patients with early breast cancer and the search for predictive biomarkers of response. The better prediction of response to neoadjuvant chemotherapy could enable the escalation or de-escalation of neoadjuvant treatment strategies, with the ultimate goal of improving the clinical management of early breast cancer. Clinico-pathological prognostic factors are currently used to estimate the potential benefit of neoadjuvant systemic treatment but are not accurate enough to allow for personalized response prediction. Other factors have recently been proposed but are not yet implementable in daily clinical practice or remain of limited utility due to the intertumoral heterogeneity of breast cancer. In this review, we describe the current knowledge about predictive factors for response to neoadjuvant chemotherapy in breast cancer patients and highlight the future perspectives that could lead to the better prediction of response, focusing on the current biomarkers used for clinical decision making and the different gene signatures that have recently been proposed for patient stratification and the prediction of response to therapies. We also discuss the intratumoral phenotypic heterogeneity in breast cancers as well as the emerging techniques and relevant pre-clinical models that could integrate this biological factor currently limiting the reliable prediction of response to neoadjuvant systemic therapy.

A comprehensive analysis of gasdermin family gene as therapeutic targets in pan-cancer

Six members of the gasdermin family are involved in various biological functions in malignant tumors. The present study aimed to perform a comprehensive analysis of gasdermin family genes in pan-cancer. Raw data was acquired from the genotype-tissue expression (GTEx) and the Cancer Genome Atlas. High inter-tumor heterogeneity in the expression between paracancerous and tumor tissues was observed across cancers. Survival analysis confirmed that the risk or protective effects of gasdermin family members on prognosis depended on the cancer types. The mutation frequency appeared to be high, and the mutation group had a worse prognosis. Besides, gasdermin family genes were associated with immune infiltrate subtypes, stromal and immune cell infiltration levels, TMB, MSI, immune checkpoint gene expression, and tumor stemness scores. Moreover, gasdermin family gene expressions affected the expressions of MMR genes and methyltransferases and could predict cancer cells sensitivity to chemotherapeutic drugs. Subsequently, the findings were double-checked in LIHC and PAAD. GSEA results indicated the gasdermin family genes mainly involved in tumor metabolism and immune microenvironment remodeling related signaling pathways. In conclusion, our findings confirmed that gasdermin family genes were potential therapeutic cancer targets in pan-cancer.

Biomanufacturing of glioblastoma organoids exhibiting hierarchical and spatially organized tumor microenvironment via transdifferentiation.

Glioblastoma (GBM) is the most aggressive type of brain tumor that originates from glioblastoma stem cells (GSCs). In the brain, GSCs are supported by a tumor microenvironment (TME) residing in the perivascular niche and the hypoxic niche. The GBM TME is highly heterogenous and exhibits complex cell-to-cell interactions. Three-dimensional tumorspheres cultured in stem cell-enriching media is often used as an in vitro model. The GBM tumorspheres retain some of the transcriptional and translational GSC features but often fails to recapitulate intertumor heterogeneity. Here, we developed a simple, matrix-free, and in vivo-like GBMorganoids (GBOs) using patient-derived xenograft GBM lines in small-scale bioreactors. Shear stress was optimized to produce highly reproducible GBOs over 1 mm diameter within 4-5 weeks. GBOs exhibited high stemness and strong cell-to-cell interactions compared to conventional tumorsphere cultures. They displayed spatial gradients of hypoxia-inducible factor 1α positive hypoxic cores where CD133-positive cells resided and spatially heterogeneous expression of NOTCH and its ligands. We also observed a self-established, hierarchically organized, and heterogeneous TME by GBM transdifferentiation into endothelial cells, pericytes, and astrocytes. Collectively, we demonstrate the ability to biomanufacture uniformly sized GBOs that recapitulate in vivo GBM TMEfeatures that can serve as an improved GBM in vitro model.

Mixed Response to Cancer Immunotherapy is Driven by Intratumor Heterogeneity and Differential Interlesion Immune Infiltration.

Several patients experience mixed responses to immunotherapies, but the biological mechanisms and clinical significance remain unclear. Our results from clinical and mouse studies underscore that intertumoral heterogeneity alters characteristics of TILs even in the same patient, leading to mixed response to immunotherapy and significant difference in the outcome.

Epigenomic interplay in tumor heterogeneity: Potential of epidrugs as adjunct therapy

“Heterogeneity” in tumor mass has immense importance in cancer progression and therapy. The impact of tumor heterogeneity is an emerging field and not yet fully explored. Tumor heterogeneity is mainly considered as intra-tumor heterogeneity and inter-tumor heterogeneity based on their origin. Intra-tumor heterogeneity refers to the discrepancy within the same cancer mass while inter-tumor heterogeneity refers to the discrepancy between different patients having the same tumor type. Both of these heterogeneity types lead to variation in the histopathological as well as clinical properties of the cancer mass which drives disease resistance towards therapeutic approaches. Cancer stem cells (CSCs) act as pinnacle progenitors for heterogeneity development along with various other genetic and epigenetic parameters that are regulating this process. In recent times epigenetic factors are one of the most studied parameters that drive oxidative stress pathways essential during cancer progression. These epigenetic changes are modulated by various epidrugs and have an impact on tumor heterogeneity. The present review summarizes various aspects of epigenetic regulation in the tumor microenvironment, oxidative stress, and progression towards tumor heterogeneity that creates complications during cancer treatment. This review also explores the possible role of epidrugs in regulating tumor heterogeneity and personalized therapy against drug resistance.