Cancers develop in complex tissue environments, which they depend on for sustained growth, invasion and metastasis. Unlike tumor cells, stromal cell types within the tumor microenvironment (TME) are genetically stable and thus represent an attractive therapeutic target with reduced risk of resistance and tumor recurrence. However, specifically disrupting the pro-tumorigenic TME is a challenging undertaking, as the TME has diverse capacities to induce both beneficial and adverse consequences for tumorigenesis. Furthermore, many studies have shown that the microenvironment is capable of normalizing tumor cells, suggesting that re-education of stromal cells, rather than targeted ablation per se, may be an effective strategy for treating cancer. Here we discuss the paradoxical roles of the TME during specific stages of cancer progression and metastasis, as well as recent therapeutic attempts to re-educate stromal cells within the TME to have anti-tumorigenic effects.

/pdf/microenvironmental-regulation-of-tumor-progression-and-4528oymlw6.pdf

Microenvironmental regulation of tumor progression and metastasis.

Accessories to the Crime: Functions of Cells Recruited to the Tumor Microenvironment

Here, the authors discuss how the immune activities of myeloid cells, such as macrophages and dendritic cells, are affected by the immunosuppressive tumour environment. They propose that tumours can evade the immune system by promoting aberrant differentiation and function of the entire myeloid system.

Coordinated regulation of myeloid cells by tumours

Tumor-associated macrophages: from mechanisms to therapy.

AACR Centennial Conference: Translational Cancer Medicine-- Nov 4-8, 2007; Singapore

PL02-05 

All cancers are due to abnormalities in DNA. The availability of the human genome sequence has led to the proposal that resequencing of cancer genomes will reveal the full complement of somatic mutations and hence all the cancer genes. To explore the nature of the information that will be derived from cancer genome sequencing we have sequenced the coding exons of the family of 518 protein kinases, ~1.3Mb DNA per cancer sample, in 210 cancers of diverse histological types. Despite the screen being directed toward the coding regions of a gene family that has previously been strongly implicated in oncogenesis, the results indicate that the majority of somatic mutations detected are “passengers”. There is considerable variation in the number and pattern of these mutations between individual cancers, indicating substantial diversity of processes of molecular evolution between cancers. The imprints of exogenous mutagenic exposures, mutagenic treatment regimes and DNA repair defects can all be seen in the distinctive mutational signatures of individual cancers. This systematic mutation screen and others have previously yielded a number of cancer genes that are frequently mutated in one or more cancer types and which are now anticancer drug targets (for example BRAF , PIK3CA , and EGFR ). However, detailed analyses of the data from our screen additionally suggest that there exist a large number of additional “driver” mutations which are distributed across a substantial number of genes. It therefore appears that cells may be able to utilise mutations in a large repertoire of potential cancer genes to acquire the neoplastic phenotype. However, many of these genes are employed only infrequently. These findings may have implications for future anticancer drug development.

Patterns of Somatic Mutation in Human Cancer Genomes

Intrinsic and acquired resistance to HER-targeting drugs occurs in a significant proportion of HER2-overexpressing breast cancers. Thus, there remains a need to identify predictive biomarkers that could improve patient selectionandcircumvent these typesofdrugresistance. Here,we reporttheidentificationofneuromedin U (NmU) as an extracellular biomarker in cells resistant to HER-targeted drugs. NmU overexpression occurred in cells withacquired or innate resistance to lapatinib, trastuzumab, neratinib, and afatinib, allofwhich displayed a similar trend upon short-term exposure, suggesting NmU induction may be an early response. An analysis of 3,489 cases of breast cancer showed NmU to be associated with poor patient outcome, particularly those with HER2-overexpressing tumors independent of established prognostic indicators. Ectopic overexpression of NmU in drug-sensitive cells conferred resistance to all HER-targeting drugs, whereas RNAi-mediated attenuation sensitized cells exhibiting acquired or innate drug resistance. Mechanistic investigations suggested that NmU acted through HSP27 as partner protein to stabilize HER2 protein levels. We also obtained evidence of functional NmUreceptorsonHER2-overexpressingcells,withtheadditionofexogenousNmUelicitinganelevationinHER2 and EGFR expression along with drug resistance. Finally, we found that NmU seemed to function in cell motility, invasion, and anoikis resistance. In vivo studies revealed that NmU attenuation impaired tumor growth and metastasis. Taken together, our results defined NmU as a candidate drug response biomarker for HER2overexpressing cancers and as a candidate therapeutic target to limit metastatic progression and improve the efficacy of HER-targeted drugs. Cancer Res; 74(14); 3821–33. � 2014 AACR.

/pdf/neuromedin-u-a-candidate-biomarker-and-therapeutic-targetto-zf6xc10z2n.pdf

Neuromedin U: A Candidate Biomarker and Therapeutic Targetto Predict and Overcome Resistance to HER-Tyrosine

Abstract To prevent the development of endocrine-resistant breast cancer, additional targeted therapies are increasingly being trialled in combination with endocrine therapy. The molecular mechanisms facilitating cancer cell survival during endocrine treatment remain unknown but could help direct selection of additional targeted therapies. We present a novel proteomic timecourse dataset, profiling potential drug targets in a population of MCF7 cells during 1 year of tamoxifen treatment. Reverse phase protein arrays profiled &gt;70 proteins across 30 timepoints. A biphasic response to tamoxifen was evident, which coincided with changes in growth rate. Tamoxifen strongly impeded cell growth for the first 160 days, followed by gradual growth recovery and eventual resistance development. The growth-impeded phase was distinguished by the phosphorylation of Stat3 (y705) and Src (y527). Tumour tissue from patients treated with neo-adjuvant endocrine therapy (&lt;4 months) also displayed increased Stat3 and Src signalling. Inhibitors of Stat3 (napabucasin) and Src (dasatinib), were effective at killing tamoxifen-treated MCF7 and T47D cells. Sensitivity to both drugs was significantly enhanced once tamoxifen had induced the growth-impeded phase. This novel proteomic resource identifies key mechanisms enabling cell survival during tamoxifen treatment. It provides valuable insight into potential drug combinations and timing that may prevent the development of endocrine resistance. 

/pdf/proteomic-time-course-of-breast-cancer-cells-highlights-169vmmwi.pdf

Proteomic time course of breast cancer cells highlights enhanced sensitivity to Stat3 and Src inhibitors prior to endocrine resistance development

/pdf/fusobacterium-nucleatum-caution-with-interpreting-historical-577vudw1sd.pdf

Fusobacterium nucleatum: caution with interpreting historical patient sample cohort.


 Introduction: Computational approaches have aided in estimating cellular composition of the tumour microenvironment. The evaluation of immune composition in tumours before treatment may predict pathologic complete response (pCR). The aim of the study was to perform a meta-analysis of HER2-positive breast cancer subjects who received neoadjuvant trastuzumab to detect associations between immune cells measured by CIBERSORT and ESTIMATE and pCR. Methods: PubMed was used to identify transcriptomic data of HER2-positive breast cancer patients who received neoadjuvant trastuzumab. Baseline data from eight neoadjuvant studies (N=338) was downloaded from GEO. Data from each study was background corrected and quantile normalised using ‘limma’ or ‘oligo’ packages in R. Immune profiles per sample was generated using computational softwares CIBERSORT and ESTIMATE, and were then linked to pCR status. Correlations between immune contexture and pCR for each study were interpreted using statistical testing. Meta-analysis by a logistic regression model was conducted on studies which passed assumptions to identify CIBERSORT immune subsets robust to pCR. Results: CIBERSORT results showed that three studies had reduced T follicular helper cells (Tfh) (Brodsky p=0.38, CHER-LOB p=0.17, TransNOAH p=0.25) and two studies had reduced plasma cells (CHER-LOB p=0.15, Brodsky p=0.38) in the pCR group, but was not significant after multiple correction. ESTIMATE analysis showed that data from two studies had elevated immune infiltration in pCR (Brodsky p=0.19, CHER-LOB p=0.10) but was not significant. A meta-analysis of pooled data from four studies (TRIO-US B07, 03-311, TransNOAH, CHER-LOB) showed that low Tfh (p=0.053, OR=0.04, CI [0.0012-0.99]) and high memory B-cells (p=0.008, OR=2126.9, CI [8.12-7.65 × 10+5]) prior to trastuzumab treatment may be associated with a better chance of achieving pCR. Conclusion: Results from our meta-analysis proposed that memory B- and T follicular helper subsets may predict a role in achieving pCR. Incorporating studies with larger sample cohorts such as the CALGB-40601 (N=265) study can achieve statistical power of this analysis.
 Citation Format: Dalal AlSultan, Alex J. Eustace, Stephen F. Madden, John Crown. In-silico approaches that detect immune contexture to trastuzumab response in neo-adjuvant studies [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P5-02-10.

Abstract P5-02-10: In-silico approaches that detect immune contexture to trastuzumab response in neo-adjuvant studies


 Introduction: Tumor infiltrating lymphocytes (TILs) have a significant effect on tumor progression and survival outcome, and serve as a potential biomarker for pathologic complete response (pCR) in neoadjuvant HER2-positive breast cancer therapy. The assessment of TIL abundance and organization prior to treatment initiation has been associated with improved survival and response in breast cancer. This study aims to assess immune contexture using in silico approaches in a meta-analysis of neoadjuvant trastuzumab therapy.
 Methods: A literature search was conducted on baseline and on-treatment mRNA data from neoadjuvant studies that enrolled patients who received HER2-targeted therapies. A total of 322 baseline samples from eight neoadjuvant datasets were retrieved from Gene Expression Omnibus (GEO) repository (0. Of these studies, two had available on-treatment samples (03-311; n=50, TRIO-US B07 (n=64). The raw data were pre-processed by normalization and background correction using ‘limma’ and ‘oligo’ packages in R. mRNA profiles of baseline and paired samples were analyzed using in silico approaches CIBERSORT and ESTIMATE. Response information was assigned to each sample to observe the proportion of immune cell contexture in pCR and non-responder (NR) groups in baseline analysis. Generalized linear mixed model (GLMM) analyses on baseline data from CIBERSORT was conducted using the ‘lme4’ package in R to investigate whether a systemic relationship of appropriate immune cell signatures occur across the pooled data. Statistical hypothesis on baseline data was applied to observe differences between pCR and NR groups. Testing on paired data was conducted to observe the differences in immune contexture between baseline and on-treatment. Results: Preliminary results of baseline analysis using CIBERSORT revealed a non-significant trend in reduced follicular helper T-cells and plasma cells in the pCR group amongst three neoadjuvant studies (Brodsky, CHER-LOB and TransNOAH). ESTIMATE analysis observed a trend in elevated immune infiltrate in pCR groups from two studies (Brodsky and CHER-LOB), but was not significant after multiple correction. Paired data analysis using CIBERSORT revealed that single-agent trastuzumab reduced activated natural killer cells (p<0.05) in the 03-311 study, whilst single-agent trastuzumab did not lead to changes in immune contexture in TRIO-US B07. Furthermore, trastuzumab in dual combination with lapatinib increased resting dendritic cells, memory B-cells and stromal cells, and reduced naive B-cells and activated dendritic cells (p<0.05) in TRIO-US. ESTIMATE analysis on paired data observed immune infiltration following trastuzumab alone in 03-311 (p=0.01) and stromal infiltration following dual combination in TRIO-US B07 (p=0.03). Neither immune subset was associated to pCR in all treatment arms of the on-treatment analysis.
 Citation Format: Dalal AlSultan, Alex J. Eustace, Stephen F. Madden, John Crown. Exploring immune contexture using computational approaches in HER2-positive breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2717.

Stephen F. Madden

Papers

Neuromedin U: A Candidate Biomarker and Therapeutic Targetto Predict and Overcome Resistance to HER-Tyrosine

Proteomic time course of breast cancer cells highlights enhanced sensitivity to Stat3 and Src inhibitors prior to endocrine resistance development

Fusobacterium nucleatum: caution with interpreting historical patient sample cohort.

Abstract P5-02-10: In-silico approaches that detect immune contexture to trastuzumab response in neo-adjuvant studies

Abstract 2717: Exploring immune contexture using computational approaches in HER2-positive breast cancer