Breast cancer hypoxia in relation to prognosis and benefit from radiotherapy after breast-conserving surgery in a large, randomised trial with long-term follow-up.

BACKGROUND: Breast-conserving surgery followed by radiotherapy is part of standard treatment for early-stage breast cancer. Hypoxia is common in cancer and may affect the benefit of radiotherapy. Cells adapt to hypoxic stress largely via the transcriptional activity of hypoxia-inducible factor (HIF)-1α. Here, we aim to determine whether tumour HIF-1α-positivity and hypoxic gene-expression signatures associated with the benefit of radiotherapy, and outcome. METHODS: Tumour HIF-1α-status and expression of hypoxic gene signatures were retrospectively analysed in a clinical trial where 1178 women with primary T1-2N0M0 breast cancer were randomised to receive postoperative radiotherapy or not and followed 15 years for recurrence and 20 years for breast cancer death. RESULTS: The benefit from radiotherapy was similar in patients with HIF-1α-positive and -negative primary tumours. Both ipsilateral and any breast cancer recurrence were more frequent in women with HIF-1α-positive primary tumours (hazard ratio, HR0-5 yrs1.9 [1.3-2.9], p = 0.003 and HR0-5 yrs = 2.0 [1.5-2.8], p < 0.0001). Tumour HIF-1α-positivity is also associated with increased breast cancer death (HR0-10 years 1.9 [1.2-2.9], p = 0.004). Ten of the 11 investigated hypoxic gene signatures correlated positively to HIF-1α-positivity, and 5 to increased rate/risk of recurrence. CONCLUSIONS: The benefit of postoperative radiotherapy persisted in patients with hypoxic primary tumours. Patients with hypoxic primary breast tumours had an increased risk of recurrence and breast cancer death.

Proteogenomic Workflow Reveals Molecular Phenotypes Related to Breast Cancer Mammographic Appearance.

Proteogenomic approaches have enabled the generat̲ion of novel information levels when compared to single omics studies although burdened by extensive experimental efforts. Here, we improved a data-independent acquisition mass spectrometry proteogenomic workflow to reveal distinct molecular features related to mammographic appearances in breast cancer. Our results reveal splicing processes detectable at the protein level and highlight quantitation and pathway complementarity between RNA and protein data. Furthermore, we confirm previously detected enrichments of molecular pathways associated with estrogen receptor-dependent activity and provide novel evidence of epithelial-to-mesenchymal activity in mammography-detected spiculated tumors. Several transcript-protein pairs displayed radically different abundances depending on the overall clinical properties of the tumor. These results demonstrate that there are differentially regulated protein networks in clinically relevant tumor subgroups, which in turn alter both cancer biology and the abundance of biomarker candidates and drug targets.

The estrogen receptor coactivator AIB1 is a new putative prognostic biomarker in ER-positive/HER2-negative invasive lobular carcinoma of the breast.

PURPOSE: According to the 2017 St Gallen surrogate definitions of the intrinsic subtypes, Ki67, progesterone receptor (PR) and Nottingham histological grade (NHG) are used for prognostic classification of estrogen receptor (ER) positive/HER2-negative breast cancer into luminal A- or luminal B-like. The aim of the present study was to investigate if additional biomarkers, related to endocrine signaling pathways, e.g., amplified in breast cancer 1 (AIB1), androgen receptor (AR), and G protein-coupled estrogen receptor (GPER), can provide complementary prognostic information in a subset of ER-positive/HER-negative invasive lobular carcinoma (ILC). METHODS: Biomarkers from 224 patients were analyzed immunohistochemically on tissue microarray. The primary endpoint was breast cancer mortality (BCM), analyzed with 10- and 25-year follow-up (FU). In addition, the prognostic value of gene expression data for these biomarkers was analyzed in three publicly available ILC datasets. RESULTS: AIB1 (high vs. low) was associated to BCM in multivariable analysis (adjusted for age, tumor size, nodal status, NHG, Ki67, luminal-like classification, and adjuvant systemic therapy) with 10-year FU (HR 6.8, 95% CI 2.3-20, P = 0.001) and 25-year FU (HR 3.0, 95% CI 1.1-7.8, P = 0.03). The evidence of a prognostic effect of AIB1 could be confirmed by linking gene expression data to outcome in independent publicly available ILC datasets. AR and GPER were neither associated to BCM with 10-year nor with 25-year FU (P > 0.33). Furthermore, Ki67 and NHG were prognostic for BCM at both 10-year and 25-year FU, whereas PR was not. CONCLUSIONS: AIB1 is a new putative prognostic biomarker in ER-positive/HER2-negative ILC.

Identification and validation of single-sample breast cancer radiosensitivity gene expression predictors.

BACKGROUND: Adjuvant radiotherapy is the standard of care after breast-conserving surgery for primary breast cancer, despite a majority of patients being over- or under-treated. In contrast to adjuvant endocrine therapy and chemotherapy, no diagnostic tests are in clinical use that can stratify patients for adjuvant radiotherapy. This study presents the development and validation of a targeted gene expression assay to predict the risk of ipsilateral breast tumor recurrence and response to adjuvant radiotherapy after breast-conserving surgery in primary breast cancer. METHODS: Fresh-frozen primary tumors from 336 patients radically (clear margins) operated on with breast-conserving surgery with or without radiotherapy were collected. Patients were split into a discovery cohort (N = 172) and a validation cohort (N = 164). Genes predicting ipsilateral breast tumor recurrence in an Illumina HT12 v4 whole transcriptome analysis were combined with genes identified in the literature (248 genes in total) to develop a targeted radiosensitivity assay on the Nanostring nCounter platform. Single-sample predictors for ipsilateral breast tumor recurrence based on a k-top scoring pairs algorithm were trained, stratified for estrogen receptor (ER) status and radiotherapy. Two previously published profiles, the radiosensitivity signature of Speers et al., and the 10-gene signature of Eschrich et al., were also included in the targeted panel. RESULTS: Derived single-sample predictors were prognostic for ipsilateral breast tumor recurrence in radiotherapy-treated ER+ patients (AUC 0.67, p = 0.01), ER+ patients without radiotherapy (AUC = 0.89, p = 0.02), and radiotherapy-treated ER- patients (AUC = 0.78, p < 0.001). Among ER+ patients, radiotherapy had an excellent effect on tumors classified as radiosensitive (p < 0.001), while radiotherapy had no effect on tumors classified as radioresistant (p = 0.36) and there was a high risk of ipsilateral breast tumor recurrence (55% at 10 years). Our single-sample predictors developed in ER+ tumors and the radiosensitivity signature correlated with proliferation, while single-sample predictors developed in ER- tumors correlated with immune response. The 10-gene signature negatively correlated with both proliferation and immune response. CONCLUSIONS: Our targeted single-sample predictors were prognostic for ipsilateral breast tumor recurrence and have the potential to stratify patients for adjuvant radiotherapy. The correlation of models with biology may explain the different performance in subgroups of breast cancer.

Cancer associated proteins in blood plasma: Determining normal variation.

Protein biomarkers have the potential to improve diagnosis, stratification of patients into treatment cohorts, follow disease progression and treatment response. One distinct group of potential biomarkers comprises proteins which have been linked to cancer, known as cancer associated proteins (CAPs). We determined the normal variation of 86 CAPs in 72 individual plasma samples collected from ten individuals using SRM mass spectrometry. Samples were collected weekly during 5 weeks from ten volunteers and over one day at nine fixed time points from three volunteers. We determined the degree of the normal variation depending on interpersonal variation, variation due to time of day, and variation over weeks and observed that the variation dependent on the time of day appeared to be the most important. Subdivision of the proteins resulted in two predominant protein groups containing 21 proteins with relatively high variation in all three factors (day, week and individual), and 22 proteins with relatively low variation in all factors. We present a strategy for prioritizing biomarker candidates for future studies based on stratification over their normal variation and have made all data publicly available. Our findings can be used to improve selection of biomarker candidates in future studies and to determine which proteins are most suitable depending on study design.

A Combined Shotgun and Targeted Mass Spectrometry Strategy for Breast Cancer Biomarker Discovery.

It is of highest importance to find proteins responsible for breast cancer dissemination, for use as biomarkers or treatment targets. We established and performed a combined nontargeted LC-MS/MS and a targeted LC-SRM workflow for discovery and validation of protein biomarkers. Eighty breast tumors, stratified for estrogen receptor status and development of distant recurrence (DR ± ), were collected. After enrichment of N-glycosylated peptides, label-free LC-MS/MS was performed on each individual tumor in triplicate. In total, 1515 glycopeptides from 778 proteins were identified and used to create a map of the breast cancer N-glycosylated proteome. Based on this specific proteome map, we constructed a 92-plex targeted label-free LC-SRM panel. These proteins were quantified across samples by LC-SRM, resulting in 10 proteins consistently differentially regulated between DR+/DR- tumors. Five proteins were further validated in a separate cohort as prognostic biomarkers at the gene expression level. We also compared the LC-SRM results to clinically reported HER2 status, demonstrating its clinical accuracy. In conclusion, we demonstrate a combined mass spectrometry strategy, at large scale on clinical samples, leading to the identification and validation of five proteins as potential biomarkers for breast cancer recurrence. All MS data are available via ProteomeXchange and PASSEL with identifiers PXD001685 and PASS00643.

Changes in glycoprotein expression between primary breast tumour and synchronous lymph node metastases or asynchronous distant metastases.

BACKGROUND: Breast cancer is a very heterogeneous disease and some patients are cured by the surgical removal of the primary tumour whilst other patients suffer from metastasis and spreading of the disease, despite adjuvant therapy. A number of prognostic and treatment predictive factors have been identified such as tumour size, oestrogen (ER) and progesterone (PgR) receptor status, human epidermal growth factor receptor type 2 (HER2) status, histological grade, Ki67 and age. Lymph node involvement is also assessed during surgery to determine if the tumour has spread which requires dissection of the axilla and adjuvant treatment. The prognostic and treatment predictive factors assessing the nature of the tumour are all routinely based on the status of the primary tumour. RESULTS: We have analysed a unique tumour set of fourteen primary breast cancer tumours with matched synchronous axillary lymph node metastases and a set of nine primary tumours with, later developed, matched distant metastases from different sites in the body. We used a pairwise tumour analysis (from the same individual) since the difference between the same tumour-type in different patients was greater. Glycopeptide capture was used in this study to selectively isolate and quantify N-linked glycopeptides from tumours mixtures and the captured glycopeptides were subjected to label-free quantitative tandem mass spectrometry analysis. Differentially expressed proteins between primary tumours and matched lymph node metastasis and distant metastasis were identified. Two of the top hits, ATPIF1 and tubulin ß-chain were validated by immunohistochemistry to be differentially regulated. CONCLUSIONS: We show that the expression of a large number of glycosylated proteins change between primary tumours and matched lymph node metastases and distant metastases, confirming that cancer cells undergo a molecular transformation during the spread to a secondary site. The proteins are part of important pathways such as cell adhesion, migration pathways and immune response giving insight into molecular changes needed for the tumour to spread. The large difference between primary tumours and lymph node and distant metastases also suggest that treatment should be based on the phenotype of the lymph node and distant metastases.

Lack of G protein-coupled estrogen receptor (GPER) in the plasma membrane is associated with excellent long-term prognosis in breast cancer.

G protein-coupled estrogen receptor (GPER), or GPR30, is a membrane receptor reported to mediate non-genomic estrogen responses. Tamoxifen is a partial agonist at GPER in vitro. Here, we investigated if GPER expression is prognostic in primary breast cancer, if the receptor is treatment-predictive for adjuvant tamoxifen, and if receptor subcellular localization has any impact on the prognostic value. Total and plasma membrane (PM) GPER expression was analyzed by immunohistochemistry in breast tumors from 742 postmenopausal lymph node-negative patients subsequently randomized for tamoxifen treatment for 2-5 years versus no systemic treatment, regardless of estrogen receptor (ER) status, and with a median follow-up of 17 years for patients free of event. PM GPER expression was a strong independent prognostic factor for poor prognosis in breast cancer without treatment-predictive information for tamoxifen. In the tamoxifen-treated ER-positive and progesterone receptor (PgR)-positive patient subgroup, the absence of PM GPER (53 % of all ER-positive tumors) predicted 91 % 20-year distant disease-free survival, compared to 73 % in the presence of GPER (p = 0.001). Total GPER expression showed positive correlations with ER and PgR and negative correlation with histological grade, but the correlations were biphasic. On the other hand, PM GPER expression showed strong negative correlations with ER and PgR, and strong positive correlation with HER2 overexpression and high histological grade. GPER overexpression and PM localization are critical events in breast cancer progression, and lack of GPER in the PM is associated with excellent long-term prognosis in ER-positive and PgR-positive tamoxifen-treated primary breast cancer.

A prostate cancer gastrointestinal transcriptional phenotype may be associated with diminished response to AR-targeted therapy.

Background: Prostate cancer is a heterogenous disease, but once it becomes metastatic it eventually becomes treatment resistant. One mechanism of resistance to AR-targeting therapy is lineage plasticity, where the tumor undergoes a transformation to an AR-indifferent phenotype, most studied in the context of neuroendocrine prostate cancer (NEPC). However, activation of additional de- or trans-differentiation programs, including a gastrointestinal (GI) gene expression program, has been suggested as an alternative method of resistance. In this study, we explored the previously identified GI prostate cancer phenotype (PCa-GI) in a large cohort of metastatic castration-resistant prostate cancer (mCRPC) patient biopsy samples. Methods: We analyzed a dataset of 634 mCRPC samples with batch effect corrected gene expression data from the West Coast Dream Team (WCDT), the East Coast Dream Team (ECDT), the Fred Hutchinson Cancer Research Center (FHCRC) and the Weill Cornell Medical center (WCM). Survival data was available from the WCDT and ECDT cohorts. We calculated a gene expression GI score using the sum of z-scores of genes from a published set of PCa-GI-defining genes (N=38). Survival analysis was performed using the Kaplan-Meier method and Cox proportional hazards regression with endpoint overall survival from time of biopsy to death of any cause. Results: We found that the PCa-GI score had a bimodal distribution, identifying a distinct set of tumors with an activated GI expression pattern. Approximately 35% of samples were classified as PCa-GI high, which was concordant with prior reports. Liver metastases had the highest median score but after excluding liver samples, 29% of the remaining samples were still classified as PCa-GI high, suggesting a distinct phenotype not exclusive to liver metastases. No correlation was observed between GI score and proliferation, AR signaling, or NEPC scores. Furthermore, the PCa-GI score was not associated with genomic alterations in AR, FOXA1, RB1, TP53 or PTEN. However, tumors with MYC amplifications showed significantly higher GI scores (p=0.0001). Patients with PCa-GI tumors had a shorter survival (HR=1.5 [1.1-2.1], p=0.02), but this result was not significant after adjusting for the liver as metastatic site (HR=1.2 [0.82-1.7], p=0.35). Patients with PCa-GI low samples had a better outcome after androgen receptor signaling inhibitors (ASI, abiraterone or enzalutamide) than other therapies (HR=0.37 [0.22-0.61], p=0.0001) while the benefit of ASI was smaller and non-significant for PCa-GI high samples (HR=0.55 [0.29-1.1], p=0.07). A differential pathway analysis identified FOXA2 signaling to be upregulated PCa-GI high tumors (FDR = 3.7 × 10-13). Conclusions: The PCa-GI phenotype is prevalent in clinical mCRPC samples and may represent a distinct biological entity. PCa-GI tumors may respond less to ASI and could offer a strategy to study novel therapeutic targets.

Integrative analysis of ultra-deep RNA-seq reveals alternative promoter usage as a mechanism of activating oncogenic programmes during prostate cancer progression.

Transcription factor (TF) proteins regulate gene activity by binding to regulatory regions, most importantly at gene promoters. Many genes have alternative promoters (APs) bound by distinct TFs. The role of differential TF activity at APs during tumour development is poorly understood. Here we show, using deep RNA sequencing in 274 biopsies of benign prostate tissue, localized prostate tumours and metastatic castration-resistant prostate cancer, that AP usage increases as tumours progress and APs are responsible for a disproportionate amount of tumour transcriptional activity. Expression of the androgen receptor (AR), the key driver of prostate tumour activity, is correlated with elevated AP usage. We identified AR, FOXA1 and MYC as potential drivers of AP activation. DNA methylation is a likely mechanism for AP activation during tumour progression and lineage plasticity. Our data suggest that prostate tumours activate APs to magnify the transcriptional impact of tumour drivers, including AR and MYC.

Transcriptomic Heterogeneity of Expansile Cribriform and Other Gleason Pattern 4 Prostate Cancer Subtypes.

BACKGROUND: Prostate cancers featuring an expansile cribriform (EC) pattern are associated with worse clinical outcomes following radical prostatectomy (RP). However, studies of the genomic characteristics of Gleason pattern 4 subtypes are limited. OBJECTIVE: To explore transcriptomic characteristics and heterogeneity within Gleason pattern 4 subtypes (fused/poorly formed, glomeruloid, small cribriform, EC/intraductal carcinoma [IDC]) and the association with biochemical recurrence (BCR)-free survival. DESIGN, SETTING, AND PARTICIPANTS: This was a retrospective cohort study including 165 men with grade group 2-4 prostate cancer who underwent RP at a single academic institution (2016-2020) and Decipher testing of the RP specimen. Patients with Gleason pattern 5 were excluded. IDC and EC patterns were grouped. Median follow-up was 2.5 yr after RP for patients without BCR. OUTCOMES MEASUREMENTS AND STATISTICAL ANALYSIS: Prompted by heterogeneity within pattern 4 subtypes identified via exploratory analyses, we investigated transcriptomic consensus clusters using partitioning around medoids and hallmark gene set scores. The primary clinical outcome was BCR, defined as two consecutive prostate-specific antigen measurements >0.2 ng/ml at least 8 wk after RP, or any additional treatment. Multivariable Cox proportional-hazards models were used to determine factors associated with BCR-free survival. RESULTS AND LIMITATIONS: In this cohort, 99/165 patients (60%) had EC and 67 experienced BCR. Exploratory analyses and clustering demonstrated transcriptomic heterogeneity within each Gleason pattern 4 subtype. In the multivariable model controlled for pattern 4 subtype, margin status, Cancer of the Prostate Risk Assessment Post-Surgical score, and Decipher score, a newly identified steroid hormone-driven cluster (hazard ratio 2.35 95% confidence interval 1.01-5.47) was associated with worse BCR-free survival. The study is limited by intermediate follow-up, no validation cohort, and lack of accounting for intratumoral and intraprostatic heterogeneity. CONCLUSIONS: Transcriptomic heterogeneity was present within and across each Gleason pattern 4 subtype, demonstrating there is additional biologic diversity not captured by histologic subtypes. This heterogeneity can be used to develop novel signatures and to classify transcriptomic subtypes, which may help in refining risk stratification following RP to further guide decision-making on adjuvant and salvage treatments. PATIENT SUMMARY: We studied prostatectomy specimens and found that tumors with similar microscopic appearance can have genetic differences that may help to predict outcomes after prostatectomy for prostate cancer. Our results demonstrate that further gene expression analysis of prostate cancer subtypes may improve risk stratification after prostatectomy. Future studies are needed to develop novel gene expression signatures and validate these findings in independent sets of patients.

Canonical AREs are tumor suppressive regulatory elements in the prostate.

The androgen receptor (AR) is the central determinant of prostate tissue identity and differentiation, controlling normal, growth-suppressive prostate-specific gene expression 1 . It is also a key driver of prostate tumorigenesis, becoming "hijacked" to drive oncogenic transcription 2-5 . However, the regulatory elements determining the execution of the growth suppressive AR transcriptional program, and whether this can be reactivated in prostate cancer (PCa) cells remains unclear. Canonical androgen response element (ARE) motifs are the classic DNA binding element for AR 6 . Here, we used a genome-wide strategy to modulate regulatory elements containing AREs to define distinct AR transcriptional programs. We find that activation of these AREs is specifically associated with differentiation and growth suppressive transcription, and this can be reactivated to cause death in AR + PCa cells. In contrast, repression of AREs is well tolerated by PCa cells, but deleterious to normal prostate cells. Finally, gene expression signatures driven by ARE activity are associated with improved prognosis and luminal phenotypes in human PCa patients. This study demonstrates that canonical AREs are responsible for a normal, growth-suppressive, lineage-specific transcriptional program, that this can be reengaged in PCa cells for potential therapeutic benefit, and genes controlled by this mechanism are clinically relevant in human PCa patients.

ZNF397 Deficiency Triggers TET2-driven Lineage Plasticity and AR-Targeted Therapy Resistance in Prostate Cancer.

Cancer cells exhibit phenotypical plasticity and epigenetic reprogramming, which allows them to evade lineage-dependent targeted treatments by adopting lineage plasticity. The underlying mechanisms by which cancer cells exploit the epigenetic regulatory machinery to acquire lineage plasticity and therapy resistance remain poorly understood. We identified Zinc Finger Protein 397 (ZNF397) as a bona fide coactivator of the androgen receptor (AR), essential for the transcriptional program governing AR-driven luminal lineage. ZNF397 deficiency facilitates the transition of cancer cell from an AR-driven luminal lineage to a Ten-Eleven Translocation 2 (TET2)-driven lineage plastic state, ultimately promoting resistance to therapies inhibiting AR signaling. Intriguingly, our findings indicate that a TET2 inhibitor can eliminate the resistance to AR targeted therapies in ZNF397-deficient tumors. These insights uncover a novel mechanism through which prostate cancer acquires lineage plasticity via epigenetic rewiring and offer promising implications for clinical interventions designed to overcome therapy resistance dictated by lineage plasticity.

Combining histological grade, TILs, and the PD-1/PD-L1 pathway to identify immunogenic tumors and de-escalate radiotherapy in early breast cancer: a secondary analysis of a randomized clinical trial.

BACKGROUND: The implementation of immunological biomarkers for radiotherapy (RT) individualization in breast cancer requires consideration of tumor-intrinsic factors. This study aimed to investigate whether the integration of histological grade, tumor-infiltrating lymphocytes (TILs), programmed cell death protein-1 (PD-1), and programmed death ligand-1 (PD-L1) can identify tumors with aggressive characteristics that can be downgraded regarding the need for RT. METHODS: The SweBCG91RT trial included 1178 patients with stage I-IIA breast cancer, randomized to breast-conserving surgery with or without adjuvant RT, and followed for a median time of 15.2 years. Immunohistochemical analyses of TILs, PD-1, and PD-L1 were performed. An activated immune response was defined as stromal TILs ≥10% and PD-1 and/or PD-L1 expression in ≥1% of lymphocytes. Tumors were categorized as high-risk or low-risk using assessments of histological grade and proliferation as measured by gene expression. The risk of ipsilateral breast tumor recurrence (IBTR) and benefit of RT were then analyzed with 10 years follow-up based on the integration of immune activation and tumor-intrinsic risk group. RESULTS: Among high-risk tumors, an activated immune infiltrate was associated with a reduced risk of IBTR (HR 0.34, 95% CI 0.16 to 0.73, p=0.006). The incidence of IBTR in this group was 12.1% (5.6-25.0) without RT and 4.4% (1.1-16.3) with RT. In contrast, the incidence of IBTR in the high-risk group without an activated immune infiltrate was 29.6% (21.4-40.2) without RT and 12.8% (6.6-23.9) with RT. Among low-risk tumors, no evidence of a favorable prognostic effect of an activated immune infiltrate was seen (HR 2.0, 95% CI 0.87 to 4.6, p=0.100). CONCLUSIONS: Integrating histological grade and immunological biomarkers can identify tumors with aggressive characteristics but a low risk of IBTR despite a lack of RT boost and systemic therapy. Among high-risk tumors, the risk reduction of IBTR conferred by an activated immune infiltrate is comparable to treatment with RT. These findings may apply to cohorts dominated by estrogen receptor-positive tumors.

Predicting response to enzalutamide and abiraterone in metastatic prostate cancer using whole-omics machine learning.

Response to androgen receptor signaling inhibitors (ARSI) varies widely in metastatic castration resistant prostate cancer (mCRPC). To improve treatment guidance, biomarkers are needed. We use whole-genomics (WGS; n = 155) with matching whole-transcriptomics (WTS; n = 113) from biopsies of ARSI-treated mCRPC patients for unbiased discovery of biomarkers and development of machine learning-based prediction models. Tumor mutational burden (q < 0.001), structural variants (q < 0.05), tandem duplications (q < 0.05) and deletions (q < 0.05) are enriched in poor responders, coupled with distinct transcriptomic expression profiles. Validating various classification models predicting treatment duration with ARSI on our internal and external mCRPC cohort reveals two best-performing models, based on the combination of prior treatment information with either the four combined enriched genomic markers or with overall transcriptomic profiles. In conclusion, predictive models combining genomic, transcriptomic, and clinical data can predict response to ARSI in mCRPC patients and, with additional optimization and prospective validation, could improve treatment guidance.

Machine Learning & Molecular Radiation Tumor Biomarkers.

Developing radiation tumor biomarkers that can guide personalized radiotherapy clinical decision making is a critical goal in the effort towards precision cancer medicine. High-throughput molecular assays paired with modern computational techniques have the potential to identify individual tumor-specific signatures and create tools that can help understand heterogenous patient outcomes in response to radiotherapy, allowing clinicians to fully benefit from the technological advances in molecular profiling and computational biology including machine learning. However, the increasingly complex nature of the data generated from high-throughput and "omics" assays require careful selection of analytical strategies. Furthermore, the power of modern machine learning techniques to detect subtle data patterns comes with special considerations to ensure that the results are generalizable. Herein, we review the computational framework of tumor biomarker development and describe commonly used machine learning approaches and how they are applied for radiation biomarker development using molecular data, as well as challenges and emerging research trends.

Proteogenomics decodes the evolution of human ipsilateral breast cancer.

Ipsilateral breast tumor recurrence (IBTR) is a clinically important event, where an isolated in-breast recurrence is a potentially curable event but associated with an increased risk of distant metastasis and breast cancer death. It remains unclear if IBTRs are associated with molecular changes that can be explored as a resource for precision medicine strategies. Here, we employed proteogenomics to analyze a cohort of 27 primary breast cancers and their matched IBTRs to define proteogenomic determinants of molecular tumor evolution. Our analyses revealed a relationship between hormonal receptors status and proliferation levels resulting in the gain of somatic mutations and copy number. This in turn re-programmed the transcriptome and proteome towards a highly replicating and genomically unstable IBTRs, possibly enhanced by APOBEC3B. In order to investigate the origins of IBTRs, a second analysis that included primaries with no recurrence pinpointed proliferation and immune infiltration as predictive of IBTR. In conclusion, our study shows that breast tumors evolve into different IBTRs depending on hormonal status and proliferation and that immune cell infiltration and Ki-67 are significantly elevated in primary tumors that develop IBTR. These results can serve as a starting point to explore markers to predict IBTR formation and stratify patients for adjuvant therapy.

Development and Validation of a Genomic Profile for the Omission of Local Adjuvant Radiation in Breast Cancer.

PURPOSE: Adjuvant radiotherapy (RT) is used for women with early-stage invasive breast cancer treated with breast-conserving surgery. However, some women with low risk of recurrence may safely be spared RT. This study aimed to identify these women using a molecular-based approach. METHODS: We analyzed two randomized trials of women with node-negative invasive breast cancer to ± RT following breast-conserving surgery: SweBCG91-RT (stage I-II, no adjuvant systemic therapy) and Princess Margaret (age 50 years or older, T1-T2, adjuvant tamoxifen). Transcriptome-wide profiling was performed (Affymetrix Human Exon 1.0 ST microarray). Patients with estrogen receptor-positive/human epidermal growth factor receptor 2-negative tumors and with gene expression data were included. The SweBCG91-RT cohort was divided into training (N = 243) and validation (N = 354) cohorts. A 16-gene signature named Profile for the Omission of Local Adjuvant Radiation (POLAR) was trained to predict locoregional recurrence (LRR) using elastic net regression. POLAR was then validated in the SweBCG91-RT validation cohort and the Princess Margaret cohort (N = 132). RESULTS: Patients categorized as POLAR low-risk without RT had a 10-year LRR of 6% (95% CI, 2 to 16) and 7% (0 to 27) in SweBCG91-RT and Princess Margaret cohorts, respectively. There was no significant benefit from RT in POLAR low-risk patients (hazard ratio [HR], 1.1 [0.39 to 3.4], P = .81, and HR, 1.5 [0.14 to 16], P = .74, respectively). Patients categorized as POLAR high-risk had a significant decreased risk of LRR with RT (HR, 0.43 [0.24 to 0.78], P = .0055, and HR, 0.25 [0.07 to 0.92], P = .038, respectively). An exploratory analysis testing for interaction between RT and POLAR in the combined validation cohort was performed (P = .066). CONCLUSION: The novel POLAR genomic signature on the basis of LRR biology may identify patients with a low risk of LRR despite not receiving RT, and thus may be candidates for RT omission.

Integrating Tumor-Intrinsic and Immunologic Factors to Identify Immunogenic Breast Cancers from a Low-Risk Cohort: Results from the Randomized SweBCG91RT Trial.

PURPOSE: The local immune infiltrate's influence on tumor progression may be closely linked to tumor-intrinsic factors. The study aimed to investigate whether integrating immunologic and tumor-intrinsic factors can identify patients from a low-risk cohort who may be candidates for radiotherapy (RT) de-escalation. EXPERIMENTAL DESIGN: The SweBCG91RT trial included 1,178 patients with stage I to IIA breast cancer, randomized to breast-conserving surgery with or without adjuvant RT, and followed for a median of 15.2 years. We trained two models designed to capture immunologic activity and immunomodulatory tumor-intrinsic qualities, respectively. We then analyzed if combining these two variables could further stratify tumors, allowing for identifying a subgroup where RT de-escalation is feasible, despite clinical indicators of a high risk of ipsilateral breast tumor recurrence (IBTR). RESULTS: The prognostic effect of the immunologic model could be predicted by the tumor-intrinsic model (Pinteraction = 0.01). By integrating measurements of the immunologic- and tumor-intrinsic models, patients who benefited from an active immune infiltrate could be identified. These patients benefited from standard RT (HR, 0.28; 95% CI, 0.09-0.85; P = 0.025) and had a 5.4% 10-year incidence of IBTR after irradiation despite high-risk genomic indicators and a low frequency of systemic therapy. In contrast, high-risk tumors without an immune infiltrate had a high 10-year incidence of IBTR despite RT treatment (19.5%; 95% CI, 12.2-30.3). CONCLUSIONS: Integrating tumor-intrinsic and immunologic factors may identify immunogenic tumors in early-stage breast cancer populations dominated by ER-positive tumors. Patients who benefit from an activated immune infiltrate may be candidates for RT de-escalation.

ZNF397 Loss Triggers TET2-driven Epigenetic Rewiring, Lineage Plasticity, and AR-targeted Therapy Resistance in AR-dependent Cancers.

Cancer cells exhibit phenotypical plasticity and epigenetic reprogramming, which allows them to evade lineage-dependent targeted treatments by adopting lineage plasticity. The underlying mechanisms by which cancer cells exploit the epigenetic regulatory machinery to acquire lineage plasticity and therapy resistance remain poorly understood. We identified Zinc Finger Protein 397 (ZNF397) as a bona fide co-activator of the androgen receptor (AR), essential for the transcriptional program governing AR-driven luminal lineage. ZNF397 deficiency facilitates the transition of cancer cell from an AR-driven luminal lineage to a Ten-Eleven Translocation 2 (TET2)-driven lineage plastic state, ultimately promoting resistance to therapies inhibiting AR signaling. Intriguingly, our findings indicate that TET2 inhibitor can eliminate the AR targeted therapies resistance in ZNF397-deficient tumors. These insights uncover a novel mechanism through which prostate and breast cancers acquire lineage plasticity via epigenetic rewiring and offer promising implications for clinical interventions designed to overcome therapy resistance dictated by lineage plasticity. Statement of Significance: This study reveals a novel epigenetic mechanism regulating tumor lineage plasticity and therapy response, enhances understanding of drug resistance and unveils a new therapeutic strategy for prostate cancer and other malignancies. Our findings also illuminate TET2's oncogenic role and mechanistically connect TET2-driven epigenetic rewiring to lineage plasticity and therapy resistance.