High Intratumoral Heterogeneity Research Articles

Classification of histological subtypes of non-small cell lung cancer using computerized tomography texture analysis

Objective: This study aimed to differentiate between the two main histological subtypes of non-small cell lung cancer using a non-invasive technique, computerized tomography texture analysis. Method: We included 53 patients. All patients were histopathologically proven non-small cell lung cancer cases. All patients underwent thorax CT scans. In CT images, the differences present in the texture features of adenocarcinoma and squamous cell carcinoma, which are the two main histological subtypes of non-small cell lung cancer, were determined by the consensus of two radiologists for computerized tomography-based texture analysis. Results: A total of 44 texture features were extracted, including 12 first-order features and 32 second-order features derived from gray-level co-occurrence matrix (GLCM), gray-level run-length matrix (GLRLM), neighborhood gray-level different matrix (NGLDM), and gray-level zone length matrix (GLZLM) features in 51 CT images. None of the evaluated texture parameters were statistically significant. However, in patients with squamous cell lung cancer, the values of Intensity Histogram, NGTDM Complexity, and Intensity Based Robust Mean Absolute Deviation higher from adenocarcinoma patients and had the highest area under the curve in roc analyses (0.727, 0.664, 0.666 respectively) Conclusion: Intensity Histogram, NGTDM Complexity, and Intensity Based Robust Mean Absolute Deviation features can be used to differentiate between the subtypes of non-small cell lung cancer, adenocarcinoma and squamous cell carcinoma. These features were highly associated with the high intratumoral heterogeneity of squamous cell lung cancer.

Machine learning based intratumor heterogeneity signature for predicting prognosis and immunotherapy benefit in stomach adenocarcinoma

Stomach adenocarcinoma (STAD) is a prevalent malignancy that is highly aggressive and heterogeneous. Intratumor heterogeneity (ITH) showed strong link to tumor progression and metastasis. High ITH may promote tumor evolution. An ITH-related signature (IRS) was created using as integrative technique including 10 machine learning methods based on TCGA, GSE15459, GSE26253, GSE62254 and GSE84437 datasets. The relevance of IRS in predicting the advantages of immunotherapy was assessed using a number of prediction scores and three immunotherapy datasets (GSE78220, IMvigor210 and GSE91061). Vitro experiments were performed to verify the biological functions of AKR1B1. The RSF + Enet (alpha = 0.1) projected model was proposed as the ideal IRS because it had the highest average C-index. The IRS demonstrated a strong performance in serving as an independent risk factor for the clinical outcome of STAD patients. It performed exceptionally well in predicting the overall survival rate of STAD patients, as seen by the TCGA cohort’s AUC of 1-, 3-, and 5-year ROC curves, which were 0.689, 0.683, and 0.669, respectively. A low IRS score demonstrated a superior response to immunotherapy, as seen by a lower TIDE score, lower immune escape score, greater TMB score, higher PD1&CTLA4 immunophenoscore, higher response rate, and improved prognosis. Common chemotherapeutic and targeted treatment regimens had lower IC50 values in the group with higher IRS scores. Vitro experiment showed that AKR1B1 was upregulated in STAD and knockdown of AKR1B1 obviously suppressed tumor cell proliferation and migration. The present investigation produced the best IRS for STAD, which may be applied to prognostication, risk stratification, and therapy planning for STAD patients.

Multiregional transcriptomic profiling provides improved prognostic insight in localized non-small cell lung cancer

Lung Cancer remains the leading cause of cancer deaths in the USA and worldwide. Non-small cell lung cancer (NSCLC) harbors high transcriptomic intratumor heterogeneity (RNA-ITH) that limits the reproducibility of expression-based prognostic models. In this study, we used multiregional RNA-seq data (880 tumor samples from 350 individuals) from both public (TRACERx) and internal (MDAMPLC) cohorts to investigate the effect of RNA-ITH on prognosis in localized NSCLC at the gene, signature, and tumor microenvironment levels. At the gene level, the maximal expression of hazardous genes (expression negatively associated with survival) but the minimal expression of protective genes (expression positively associated with survival) across different regions within a tumor were more prognostic than the average expression. Following that, we examined whether multiregional expression profiling can improve the performance of prognostic signatures. We investigated 11 gene signatures collected from previous publications and one signature developed in this study. For all of them, the prognostic prediction accuracy can be significantly improved by converting the regional expression of signature genes into sample-specific expression with a simple function—taking the maximal expression of hazardous genes and the minimal expression of protective genes. In the tumor microenvironment, we found a similar rule also seems applicable to immune ITH. We calculated the infiltration levels of major immune cell types in each region of a sample based on expression deconvolution. Prognostic analysis indicated that the region with the lowest infiltration level of protective or highest infiltration level of hazardous immune cells determined the prognosis of NSCLC patients. Our study highlighted the impact of RNA-ITH on the prognostication of NSCLC, which should be taken into consideration to optimize the design and application of expression-based prognostic biomarkers and models. Multiregional assays have the great potential to significantly improve their applications to prognostic stratification.

The RAS/BRAF genes status in patients with colorectal cancer (review)

Colorectal cancer (CRC) is the third in prevalence among oncological diseases worldwide and second in the structure of oncological mortality. Genetic assessment of CRC is a necessary stage during selecting further treatment for patients. Many studies demonstrate a diverse distribution of mutations in the KRAS, NRAS, and BRAF genes in CRC. A critical literature review was conducted in order to systematize data on the mutational profile and genetic heterogeneity of these driver mutations in Russian patients with CRC. Articles were searched for in open databases. Totally 17 Russian studies and 3 English meta-analyses were analyzed for comparison with Russian data. Mutations in the KRAS, NRAS, and BRAF genes, according to Russian and international studies, are found in 40 %, 4 %, and 7 % in CRC patients, respectively. The frequency and specific localization of mutations may depend on the geographical location and nationality of the cohort. High intertumoral and intratumoral heterogeneity in CRC, especially in KRAS gene mutations, significantly influences the choice of further therapy and underscores the need for more detailed study of the mutational profile of the primary tumor, affected lymph nodes, and distant metastases. In Russia, several molecular genetic methods are used to determine somatic mutations in CRC with different sensitivity and specificity, the most common is real-time PCR. More accurate diagnostic methods include digital droplet PCR, Sanger sequencing, and next-generation sequencing, but each method has its limitations that must be considered when planning diagnostics and research. The promising directions in personalized oncology is the study of gene copy number variations, which may contribute to the development of new methods for treating CRC in the future. Despite the large number of studies, some aspects of the mutational profile of CRC in Russian studies remain poorly understood, which is why further research is needed on patients with colorectal cancer in Russia.

Type I interferon signaling pathway enhances immune-checkpoint inhibition in KRAS mutant lung tumors

Lung cancer is the leading cause of cancer mortality worldwide. KRAS oncogenes are responsible for at least a quarter of lung adenocarcinomas, the main subtype of lung cancer. After four decades of intense research, selective inhibitors of KRAS oncoproteins are finally reaching the clinic. Yet, their effect on overall survival is limited due to the rapid appearance of drug resistance, a likely consequence of the high intratumoral heterogeneity characteristic of these tumors. In this study, we have attempted to identify those functional alterations that result from KRAS oncoprotein expression during the earliest stages of tumor development. Such functional changes are likely to be maintained during the entire process of tumor progression regardless of additional co-occurring mutations. Single-cell RNA sequencing analysis of murine alveolar type 2 cells expressing a resident Kras oncogene revealed impairment of the type I interferon pathway, a feature maintained throughout tumor progression. This alteration was also present in advanced murine and human tumors harboring additional mutations in the p53 or LKB1 tumor suppressors. Restoration of type I interferon (IFN) signaling by IFN-β or constitutive active stimulator of interferon genes (STING) expression had a profound influence on the tumor microenvironment, switching them from immunologically "cold" to immunologically "hot" tumors. Therefore, enhancement of the type I IFN pathway predisposes KRAS mutant lung tumors to immunotherapy treatments, regardless of co-occurring mutations in p53 or LKB1.

Revealing Cellular Heterogeneity and Key Regulatory Factors of Triple-Negative Breast Cancer through Single-Cell RNA Sequencing.

Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer (BC). TNBC has a poor prognosis due to high intratumoral heterogeneity and metastasis, pointing to the need to explore distinct molecular subtypes and gene regulatory networks. The scRNA-seq data of five primary BC samples were downloaded from the Gene Expression Omnibus (GEO) database. Clustering was performed based on filtered and normalized data using the Seurat R package to identify marker genes, which were subsequently annotated to each subset using the CellMarker database. AUCell R package was applied to calculate the hallmark score for each epithelial cell. Marker genes of each subset were screened with FindAllMarkers and their biological functions were analyzed using the Database for Annotation Visualization and Integrated Discovery (DAVID) database. Next, cell-cell communication was performed with the CellChat R package. To identify the key regulatory genes, single-cell regulatory network inference and clustering (SCENIC) analysis was conducted. Finally, the expression and potential biological functions of the key regulatory factors were verified through cellular experiments. A total of 29,101 cells were classified into nine cell subsets, namely, Fibroblasts, Fibroepithelial cells, Epithelial cells 1, Epithelial cells 2, Epithelial cells 3, Endothelial cells, T cells, Plasma B cells and Macrophages. Particularly, the epithelial cells had a higher proportion and higher transforming growth factor-β (TGF-β) activity in the TNBC pathotype as compared to the non-TNBC pathotype. Furthermore, four epithelial cell subsets (marked as Stearoyl-CoA Desaturase (SCD1), marker of proliferation Ki67 (MKI67), Annexin A3 (ANXA3) and aquaporin 5 (AQP5)) were identified as having the greatest impact on the TNBC pathotype. Cell-cell interaction analysis revealed that ANXA3-epithelial cell subset suppressed the T cell function through different mechanisms. C-fos gene (FOS) and X-box binding protein 1 (XBP1) were considered critical regulons involved in TNBC progression. Notably, cellular experiments demonstrated that silencing XBP1 and overexpressing FOS inhibited cancer cell invasion. The four epithelial cell subsets and two critical regulons identified based on the scRNA-seq data could help explore the underlying intratumoral heterogeneity molecular mechanism and develop effective therapies for TNBC.

Spatial intra-tumour heterogeneity and treatment-induced genomic evolution in oesophageal adenocarcinoma: implications for prognosis and therapy

BackgroundOesophageal adenocarcinoma (OAC) is a highly heterogeneous cancer with poor survival. Standard curative treatment is chemotherapy with or without radiotherapy followed by oesophagectomy. Genomic heterogeneity is a feature of OAC and has been linked to treatment resistance.MethodsWhole-genome sequencing data from 59 treatment-naïve and 18 post-treatment samples from 29 OAC patients was analysed. Twenty-seven of these were enrolled in the DOCTOR trial, sponsored by the Australasian Gastro-Intestinal Trials Group. Two biopsies from each treatment-naïve tumour were assessed to define ‘shared’ (between both samples) and ‘private’ (present in one sample) mutations.ResultsMutational signatures SBS2/13 (APOBEC) and SBS3 (BRCA) were almost exclusively detected in private mutation populations of treatment-naïve tumours. Patients presenting these signatures had significantly worse disease specific survival. Furthermore, mutational signatures associated with platinum-based chemotherapy treatment as well as high platinum enrichment scores were only detected in post-treatment samples. Additionally, clones with high putative neoantigen binding scores were detected in some treatment-naïve samples suggesting immunoediting of clones.ConclusionsThis study demonstrates the high intra-tumour heterogeneity in OAC, as well as indicators for treatment-induced changes during tumour evolution. Intra-tumour heterogeneity remains a problem for successful treatment strategies in OAC.

Machine learning developed an intratumor heterogeneity signature for predicting clinical outcome and immunotherapy benefit in bladder cancer.

Bladder cancer is a common malignancy with high invasion and poor clinical outcome. Intratumor heterogeneity (ITH) is linked to cancer progression and metastasis and high ITH can accelerate tumor evolution. Our objective is to develop an ITH-related signature (IRS) for predicting clinical outcome and immunotherapy benefit in bladder cancer. Integrative procedure containing ten machine learning methods was applied to develop an IRS with The Cancer Genome Atlas (TCGA), gene series expression (GSE)13507, GSE31684, GSE32984 and GSE48276 datasets. To evaluate the performance of IRS in predicting the immunotherapy benefit, we also used several predicting scores and three immunotherapy datasets, including GSE91061, GSE78220 and IMvigor210. The predicting model constructed with Enet (alpha =0.2) algorithm had a highest average C-index of 0.69, which was suggested as the optimal IRS. As an independent risk factor for bladder cancer, IRS had a powerful performance in predicting the overall survival (OS) rate of patients, with an area under curve of 1-, 3- and 5-year receiver operating characteristic (ROC) curve being 0.744, 0.791 and 0.816 in TCGA dataset. Bladder cancer patients with low IRS score presented with a higher level of immune-activated cells, cytolytic function and T cell co-stimulation. We also found a lower tumor immune dysfunction and exclusion (TIDE) score, lower immune escape score, higher programmed cell death protein 1 (PD-1) & cytotoxic T-lymphocyte associated protein 4 immunophenoscore, higher tumor mutation burden (TMB) score, higher response rate and better prognosis in bladder cancer with low IRS score. Bladder cancer cases with high IRS score had a higher half maximal inhibitory concentration value of common chemotherapy and targeted therapy regimens. The current study developed an optimal IRS for bladder cancer patients, which acted as an indicator for predicting prognosis, stratifying risk and guiding treatment for bladder cancer patients. Further analysis should be focused on the exploration the differentially expressed genes (DEGs) and related underlying mechanism mediating the development of bladder cancer in different IRS score group.

Visual Intratumor Heterogeneity and Breast Tumor Progression.

High intratumoral heterogeneity is thought to be a poor prognostic indicator. However, the source of heterogeneity may also be important, as genomic heterogeneity is not always reflected in histologic or 'visual' heterogeneity. We aimed to develop a predictor of histologic heterogeneity and evaluate its association with outcomes and molecular heterogeneity. We used VGG16 to train an image classifier to identify unique, patient-specific visual features in 1655 breast tumors (5907 core images) from the Carolina Breast Cancer Study (CBCS). Extracted features for images, as well as the epithelial and stromal image components, were hierarchically clustered, and visual heterogeneity was defined as a greater distance between images from the same patient. We assessed the association between visual heterogeneity, clinical features, and DNA-based molecular heterogeneity using generalized linear models, and we used Cox models to estimate the association between visual heterogeneity and tumor recurrence. Basal-like and ER-negative tumors were more likely to have low visual heterogeneity, as were the tumors from younger and Black women. Less heterogeneous tumors had a higher risk of recurrence (hazard ratio = 1.62, 95% confidence interval = 1.22-2.16), and were more likely to come from patients whose tumors were comprised of only one subclone or had a TP53 mutation. Associations were similar regardless of whether the image was based on stroma, epithelium, or both. Histologic heterogeneity adds complementary information to commonly used molecular indicators, with low heterogeneity predicting worse outcomes. Future work integrating multiple sources of heterogeneity may provide a more comprehensive understanding of tumor progression.

Clinical relevance of circulating tumor DNA in ovarian cancer: current issues and future opportunities.

Ovarian cancer (OC) is the most lethal gynecologic malignancy worldwide. Due to the lack of effective screening and early detection strategies, many patients with OC are diagnosed with advanced disease, where treatment is rarely curative. Moreover, OC is characterized by high intratumor heterogeneity, which represents a major barrier to the development of effective treatments. Conventional tumor biopsy and blood-based biomarkers, such as cancer antigen 125 (CA125), have different limitations. Liquid biopsy has recently emerged as an attractive and promising area of investigation in oncology, due to its minimally invasive, safe, comprehensive, and real-time dynamic nature. Preliminary evidence suggests a potential role of liquid biopsy to refine OC management, by improving screening, early diagnosis, assessment of response to treatment, detection, and profiling of drug resistance. The current knowledge and the potential clinical value of liquid biopsy in OC is discussed in this review to provide an overview of the clinical settings in which its use might support and improve diagnosis and treatment.

Whole exome sequencing analysis of intratumoral heterogeneity, tumor neoantigen burden and human leukocyte antigen loss of heterozygosity in HCC.

e16003 Background: Hepatocellular Carcinoma (HCC) patients has a high postoperative recurrence within 2 years and a low 5-year survival rate. However, molecular mechanisms for early recurrence are poorly understood. Immune checkpoint blockades (ICBs) show clinical benefits in HCC, with the immune microenvironment influencing ICBs therapeutic effects. Exploring the relationship between intratumoral heterogeneity (ITH), tumor neoantigen burden (TNB), and human leukocyte antigen loss of heterozygosity (HLA LOH) can deepen our understanding of the immune evasion mechanisms. Methods: In this study, whole exome sequencing (WES) was employed to analyze tumor specimens and matched peripheral blood controls derived from a cohort of 235 HCC patients. PD-L1 expression levels were assessed in the samples using immunohistochemistry. NetMHCpan was applied to predict neoantigen and quantified the peptide affinity of MHC-I genes measured by IC50. Neoantigen-MHC affinity was categorized as strong (IC50≤50nM), weak (50nM < IC50≤500nM), and negative (IC50 > 500nM). TNB was defined by the number of high affinity neoantigens per megabase in WES. Analysis of LOH was performed on HLA-I class genes and categorized as strong positive, weak positive, and negative groups. We used PyClone to conduct ITH analysis to assess the distribution of multiple subclones within a tumor. The average Cancer Cell Fraction (CCF) for each somatic mutation cluster was calculated, and these clusters were classified into major clones and subclones. Results: In 235 HCC samples, median TMB and TNB were 2.48 Muts/Mb and 0.30 Neos/Mb. Only 6.81% exhibited TMB-H (TMB≥10 Muts/Mb). TMB and TNB are significantly positively correlated (p < 0.0001). HLA LOH occurred in 19.57% HCC patients, with high LOH samples having more high-affinity neoantigens (mean TNB 1.65 Neos/Mb). ITH analysis showed that 83.83% samples harbored subclonal clusters. HCC samples were divided into high (ITH≥0.908) and low (ITH < 0.908) groups according to the median ITH of 0.908. High ITH group had higher TNB (median 0.43 vs 0.20 Neos/Mb) , more HLA LOH (9.24% vs 5.17% strong positive LOH). The high ITH groups exhibited a lower percentage of samples with elevated PD-L1 expression (14.29% vs 25.86%). The Combined Positive Score (CPS) revealed a significant difference between the groups (Fisher's test p = 0.03). Conclusions: In HCC, the high ITH group exhibited a higher proportion of HLA LOH compared to the low ITH group. Moreover, a decreased proportion of PD-L1 positive samples was observed in the high ITH group, suggesting that high ITH may be a key factor influencing treatment failure in immunotherapy. ITH analysis demonstrated a potential multi-subclonal origin of recurrent tumor cells, which is associated with immune escape, tumor malignancy,as well as the development of resistance.

Immune cell infiltration and inflammatory landscape in primary brain tumours

BackgroundPrimary malignant brain tumours are more than one-third of all brain tumours and despite the molecular investigation to identify cancer driver mutations, the current therapeutic options available are challenging due to high intratumour heterogeneity. In addition, an immunosuppressive and inflammatory tumour microenvironment strengthens cancer progression. Therefore, we defined an immune and inflammatory profiling of meningioma and glial tumours to elucidate the role of the immune infiltration in these cancer types.MethodsUsing tissue microarrays of 158 brain tumour samples, we assessed CD3, CD4, CD8, CD20, CD138, Granzyme B (GzmB), 5-Lipoxygenase (5-LOX), Programmed Death-Ligand 1 (PD-L1), O-6-Methylguanine-DNA Methyltransferase (MGMT) and Transglutaminase 2 (TG2) expression by immunohistochemistry (IHC). IHC results were correlated using a Spearman correlation matrix. Transcript expression, correlation, and overall survival (OS) analyses were evaluated using public datasets available on GEPIA2 in Glioblastoma (GBM) and Lower Grade Glioma (LGG) cohorts.ResultsSeven out of ten markers showed a significantly different IHC expression in at least one of the evaluated cohorts whereas CD3, CD4 and 5-LOX were differentially expressed between GBMs and astrocytomas. Correlation matrix analysis revealed that 5-LOX and GzmB expression were associated in both meningiomas and GBMs, whereas 5-LOX expression was significantly and positively correlated to TG2 in both meningioma and astrocytoma cohorts. These findings were confirmed with the correlation analysis of TCGA-GBM and LGG datasets. Profiling of mRNA levels indicated a significant increase in CD3 (CD3D, CD3E), and CD138 (SDC1) expression in GBM compared to control tissues. CD4 and 5-LOX (ALOX5) mRNA levels were significantly more expressed in tumour samples than in normal tissues in both GBM and LGG. In GBM cohort, GzmB (GZMB), SDC1 and MGMT gene expression predicted a poor overall survival (OS). Moreover, in LGG cohort, an increased expression of CD3 (CD3D, CD3E, CD3G), CD8 (CD8A), GZMB, CD20 (MS4A1), SDC1, PD-L1, ALOX5, and TG2 (TGM2) genes was associated with worse OS.ConclusionsOur data have revealed that there is a positive and significant correlation between the expression of 5-LOX and GzmB, both at RNA and protein level. Further evaluation is needed to understand the interplay of 5-LOX and immune infiltration in glioma progression.

Glioblastoma microenvironment-from biology to therapy.

Glioblastoma (GBM) is the most aggressive primary brain cancer. These tumors exhibit high intertumoral and intratumoral heterogeneity in neoplastic and nonneoplastic compartments, low lymphocyte infiltration, and high abundance of myeloid subsets that together create a highly protumorigenic immunosuppressive microenvironment. Moreover, heterogeneous GBM cells infiltrate adjacent brain tissue, remodeling the neural microenvironment to foster tumor electrochemical coupling with neurons and metabolic coupling with nonneoplastic astrocytes, thereby driving growth. Here, we review heterogeneity in the GBM microenvironment and its role in low-to-high-grade glioma transition, concluding with a discussion of the challenges of therapeutically targeting the tumor microenvironment and outlining future research opportunities.

Landscape and Treatment Options of Shapeshifting Small Cell Lung Cancer.

Small cell lung cancer (SCLC) is a deadly neuroendocrine malignancy, notorious for its rapid tumor growth, early metastasis, and relatively "cold" immune environment. Only standard chemotherapies and a few immune checkpoint inhibitors have been approved for SCLC treatment, revealing an urgent need for novel therapeutic approaches. Moreover, SCLC has been recently recognized as a malignancy with high intratumoral and intertumoral heterogeneity, which explains the modest response rate in some patients and the early relapse. Molecular subtypes defined by the expression of lineage-specific transcription factors (ASCL1, NEUROD1, POU2F3, and, in some studies, YAP1) or immune-related genes display different degrees of neuroendocrine differentiation, immune cell infiltration, and response to treatment. Despite the complexity of this malignancy, a few biomarkers and targets have been identified and many promising drugs are currently undergoing clinical trials. In this review, we integrate the current progress on the genomic landscape of this shapeshifting malignancy, the characteristics and treatment vulnerabilities of each subtype, and promising drugs in clinical phases.

Development of Personalized Strategies for Precisely Battling Malignant Melanoma.

Melanoma is the most severe and fatal form of skin cancer, resulting from multiple gene mutations with high intra-tumor and inter-tumor molecular heterogeneity. Treatment options for patients whose disease has progressed beyond the ability for surgical resection rely on currently accepted standard therapies, notably immune checkpoint inhibitors and targeted therapies. Acquired resistance to these therapies and treatment-associated toxicity necessitate exploring novel strategies, especially those that can be personalized for specific patients and/or populations. Here, we review the current landscape and progress of standard therapies and explore what personalized oncology techniques may entail in the scope of melanoma. Our purpose is to provide an up-to-date summary of the tools at our disposal that work to circumvent the common barriers faced when battling melanoma.

Abstract PO5-14-09: Does transcriptome based DEPTH2 score reflect intratumor heterogeneity in breast cancer patients?

Abstract Background: Intratumor heterogeneity (ITH) refers to the presence of distinct cancer cell populations with different clones within a single tumor mass. Tumors with high ITH are more prone to progression, exhibit resistance to therapies, and are associated with an unfavorable prognosis. Therefore, evaluation of ITH is anticipated to serve as a breakthrough biomarker for prognosis and treatment strategies. Several computational algorithms have been proposed to quantify ITH. However, with the exception of DEPTH2, all of these algorithms require both DNA and RNA-sequence data from the same tumor, which can be challenging. In this study, we investigated whether DEPTH2 which solely analyzes RNA-sequence data, accurately reflects the biological characteristics of ITH. Methods: We analyzed clinicopathological and gene expression data from a total of 6573 breast cancer patients from several large independent cohorts: METABRIC (n = 1903), GSE96058 (n = 3273), GSE21974 (n = 57), GSE28844 (n = 61), GSE87455 (n = 153), GSE180280 (n = 57), and The Cancer Genome Atlas (TCGA, n = 1069). Results: DEPTH2 score was high in Triple Negative Breast Cancer (TNBC) subtype (p < 0.001), but no consistent correlation was observed with lymph node or distal metastasis. Higher DEPTH2 score was associated with cell proliferation, as evidenced by higher Nottingham histological grade and Ki67 gene expression (both p < 0.001). In agreement, high DEPTH2 tumors enriched all cell proliferation-related Hallmark gene sets such as E2F targets, G2M checkpoint, MYC targets v1 and v2, and Mitotic Spindle (FDR < 0.25). Additionally, high DEPTH2 tumors exhibited reduced immune cell infiltrations, such as CD8, CD4, Th1, Th2, B cells, and macrophages, and increased infiltrations of stromal cells, such as adipocytes, fibroblasts, blood and lymphatic endothelial cells (all p < 0.05). In TCGA cohort, DEPTH2 score exhibited a similar trend to intratumoral heterogeneity, homologous recombination deficiency, fraction altered, silent and nonsilent mutations, as well as SNV and Indel neoantigens. However, the Pearson’s correlation coefficient was very weak (p < 0.05). DEPTH2 score decreased in the GSE21974 and GSE87455 cohorts after neoadjuvant chemotherapy (NAC), whereas no change was observed in the GSE28844 and GSE180280 cohorts. DEPTH2 high tumors showed a lower rate of pathologic complete response (pCR) after NAC in estrogen receptor (ER)+HER2- subtype across all cohorts, however, opposite pattern was observed in the HER2+ and TNBC subtypes in all cohorts. Lastly, high DEPTH2 score was associated with lower disease free and overall survival in METABRIC and GSE96058 (p < 0.05), but not in the TCGA cohort. Conclusions: Our findings suggest that DEPTH2 score may not completely capture the biological characteristics associated with intratumor heterogeneity. Citation Format: Kohei Chida, Rongrong Wu, Arya Mariam Roy, Takashi Ishikawa, Kazuaki Takabe. Does transcriptome based DEPTH2 score reflect intratumor heterogeneity in breast cancer patients? [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO5-14-09.

Abstract PO2-23-08: High intratumor heterogeneity induced PSME2 confers endocrine resistance via ERα PARylation in hormone receptor-positive and HER2-negative breast cancer

Abstract Background: Hormone receptor-positive and HER2-negative breast cancer, characterized by its significant intratumor heterogeneity (ITH), poses increased recurrence, metastasis risk, and endocrine resistance. A comprehensive understanding of the genomic and biological characteristics underlying ITH is crucial for the development of effective therapeutic strategies. Methods: We leveraged the multiomics data from our large cohort of 381 hormone receptor-positive and HER2-negative breast tumors, supplemented with single-cell sequencing (scRNA-seq) data from 9 individual samples, to investigate ITH and its associated molecular features. Mechanistic investigations were conducted using Stable Isotope Labeling by Amino Acids in Cell culture (SILAC) proteomics, co-immunoprecipitation (Co-IP), Chromatin Immunoprecipitation followed by quantitative PCR (ChIP-qPCR), and dual-luciferase reporter assays. We specifically focused on the role of Proteasome activator subunit beta (PSME2), a potential regulator of drug resistance and metastasis. Results: We quantified the degree of ITH at sample level using multi-omics and scRNA-seq data and observed a correlation between higher ITH levels, increased genomic instability, upregulation of the STING type-I-interferon-dependent pathway, and poor efficacy of endocrine therapy. Both bulk and single-cell data revealed an enrichment of PSME2, associated with type-I interferon, in groups exhibiting high ITH. Patients with elevated PSME2 expression manifested a poorer prognosis and diminished responsiveness to endocrine therapy. Within the context of ITH, we discovered that IFN-I transcriptionally activated PSME2 via STAT1. Further investigation revealed a complex interplay among PSME2, PARP1, and EWS, wherein PSME2-mediated degradation of EWS relieved the transcriptional repression of PARP1, resulting in its overexpression. This series of events, orchestrated by PSME2, led to ERα PARylation and promoted tamoxifen resistance. In subsequent clinical translation studies employing mouse xenograft, patient-derived organoid (PDO), and patient-derived xenograft (PDX) models, we demonstrated that PARP1 inhibitors could effectively mitigate tamoxifen resistance induced by high PSME2 expression, providing new insights into therapeutic strategies. Conclusions: Our study highlights the importance of understanding ITH in hormone receptor-positive and HER2-negative breast cancer and identifies PSME2 as a key player in endocrine resistance and patient prognosis. The application of PARP1 inhibitors shows promise in improving treatment outcomes in tumors with elevated ITH and PSME2 expression. Working Modle Citation Format: Li-Ping Ge, Zi-Yu Wang, Xi Jin, Yi-Zhou Jiang, Zhi-Ming Shao. High intratumor heterogeneity induced PSME2 confers endocrine resistance via ERα PARylation in hormone receptor-positive and HER2-negative breast cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO2-23-08.

Abstract LB223: The molecular landscape of injury-induced mammary epithelial cell fate switching

Abstract The most aggressive cancers, such as triple negative basal-like breast cancer (TNBC), have high intratumoral heterogeneity that is often attributed to cell state reprogramming and contributes to cancer progression, treatment resistance, and ultimately cancer death. Tissue injury and microenvironmental changes can cause adult differentiated cells to acquire a plastic “developmentally unstable hybrid cell state” (DUHCS) enabling transdifferentiation into other cell types to effect repair. Yet, the relevant mechanisms that enable cell state reprogramming to arise remain under-explored. Here, we used CRISPR mediated homologous recombination to generate mice in which the mammary basal and luminal cells could be distinguished by their expression of Krt14-mClover-NLS or Krt18-tdTomato-NLS, respectively. We used this novel system to identify mammary epithelial cells undergoing cell state transitions in real time. Using a transplantation paradigm, we found that transplanted basal cells rapidly exhibited a DUHCS resembling mammary embryonic progenitors expressing Sox11, a tightly regulated differentiation factor shut off before birth. We discovered that Sox11 is also expressed in many murine models of TNBC and in single cell transcriptomes from untreated human BRCA1 mutant TNBCs. This suggests that Sox11-expressing cells might be developmentally plastic intermediates in TNBC malignant progression. In a preliminary cohort of patient-derived xenografts from TNBC patients diagnosed at different stages, we detected SOX11-expressing cells in earlier but not in advanced stages. Re-expression of Sox11 in TNBC is consistent with TNBCs being transcriptomically related to fetal mammary stem cells and p53 dysfunction resulting in enhanced cellular plasticity. Taken together, these studies highlight a role for mammary epithelial cell state reprogramming in early breast tumorigenesis, and reveals actionable steps to mitigate tumor heterogeneity by halting tumor progression. Citation Format: Queralt Vallmajó Martín, Nikki K. Lytle, Divya Murali, Sumana Srinivasan, Zhibo Ma, Kavitha Mukund, Christopher Dravis, Liliana Zamora, Ana Peterson, Galina Khramtsova, Funmi Olopade, Shankar Subramaniam, Geoffrey M. Wahl. The molecular landscape of injury-induced mammary epithelial cell fate switching [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB223.

High Ki67 Gene Expression Is Associated With Aggressive Phenotype in Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) with high Ki67 protein expression, the most commonly used cell proliferation marker, is associated with an aggressive biologic phenotype; however, conventional immunostaining is hampered by variability in institutional protocol, specific antibody probe, and by assessor subjectivity. To this end, we hypothesized that Ki67 gene (MKi67) expression would identify highly proliferative HCC, and clarify its association with oncologic outcome, tumor progression, and immune cell population in the tumor microenvironment (TME). Furthermore, we sought to identify the cell-cycle gene expression profile that confers this aggressive phenotype. A total of 473 HCC patients with clinicopathological data associated with transcriptome were selected for this study: 358 patients from The Cancer Genome Atlas (TCGA) as the testing cohort, and 115 from GSE76427 as the validation cohort. Each cohort was divided into a highly proliferative group (MKi67-high) and the low MKi67 group (MKi67-low) by the median of Ki67 gene (MKi67) expression levels. MKi67-high HCC patients had worse disease-free survival (DFS), disease-specific survival (DSS), and overall survival (OS) independent of histological grade in the TCGA cohort. MKi67 expression correlated with histological grade and tumor size. MKi67 expression increased throughout the HCC carcinomatous sequence from normal liver, cirrhotic liver, early HCC, and advanced HCC. MKi67-high HCC was associated with higher intratumor heterogeneity, homologous recombination deficiency, and altered fraction as well as intratumoral infiltration of T helper type 1 (Th1) and Th2 cells, but lower interferon-gamma response and M2 macrophage infiltration. Cell proliferation-related gene sets in the Hallmark collection (E2F targets, G2M checkpoint, Myc target v1 and mitotic spindle), MTORC1 signaling, DNA repair, PI3K MTOR signaling, and unfolded protein response were all enriched in the MKi67-high HCC (false discovery rate (FDR) < 0.25). High MKi67 gene expression identified highly proliferative HCC with aggressive biology involving classical pathways in cell cycle regulation and DNA repair, as well as poor overall oncologic outcomes. This suggests potential for personalized treatment strategies, but validation and refinement of these observations require further research to elucidate the underlying mechanisms and validate therapeutic targeting of these pathways in MKi67-high HCC tumors.

Molecular and immune characterization of Chinese early-stage non-squamous non-small cell lung cancer: a multi-omics cohort study.

Albeit considered with superior survival, around 30% of the early-stage non-squamous non-small cell lung cancer (Ns-NSCLC) patients relapse within 5 years, suggesting unique biology. However, the biological characteristics of early-stage Ns-NSCLC, especially in the Chinese population, are still unclear. Multi-omics interrogation of early-stage Ns-NSCLC (stage I-III), paired blood samples and normal lung tissues (n=76) by whole-exome sequencing (WES), RNA sequencing, and T-cell receptor (TCR) sequencing were conducted. An average of 128 exonic mutations were identified, and the most frequently mutant gene was EGFR (55%), followed by TP53 (37%) and TTN (26%). Mutations in MUC17, ABCA2, PDE4DIP, and MYO18B predicted significantly unfavorable disease-free survival (DFS). Moreover, cytobands amplifications in 8q24.3, 14q13.1, 14q11.2, and deletion in 3p21.1 were highlighted in recurrent cases. Higher incidence of human leukocyte antigen loss of heterozygosity (HLA-LOH), higher tumor mutational burden (TMB) and tumor neoantigen burden (TNB) were identified in ever-smokers than never-smokers. HLA-LOH also correlated with higher TMB, TNB, intratumoral heterogeneity (ITH), and whole chromosomal instability (wCIN) scores. Interestingly, higher ITH was an independent predictor of better DFS in early-stage Ns-NSCLC. Up-regulation of immune-related genes, including CRABP2, ULBP2, IL31RA, and IL1A, independently portended a dismal prognosis. Enhanced TCR diversity of peripheral blood mononuclear cells (PBMCs) predicted better prognosis, indicative of a noninvasive method for relapse surveillance. Eventually, seven machine-learning (ML) algorithms were employed to evaluate the predictive accuracy of clinical, genomic, transcriptomic, and TCR repertoire data on DFS, showing that clinical and RNA features combination in the random forest (RF) algorithm, with area under the curve (AUC) of 97.5% and 83.3% in the training and testing cohort, respectively, significantly outperformed other methods. This study comprehensively profiled the genomic, transcriptomic, and TCR repertoire spectrums of Chinese early-stage Ns-NSCLC, shedding light on biological underpinnings and candidate biomarkers for prognosis development.