Real-world Evidence of Diagnostic Testing and Treatment Patterns in US Patients With Breast Cancer With Implications for Treatment Biomarkers From RNA Sequencing Data

Long-term breast cancer response to CDK4/6 inhibition defined by TP53-mediated geroconversion

Inhibition of CDK4/6 kinases has led to improved outcomes in breast cancer. Nevertheless, only a minority of patients experience long-term disease control. Using a large, clinically annotated cohort of patients with metastatic hormone receptor-positive (HR+) breast cancer, we identify TP53 loss (27.6%) and MDM2 amplification (6.4%) to be associated with lack of long-term disease control. Human breast cancer models reveal that p53 loss does not alter CDK4/6 activity or G1 blockade but instead promotes drug-insensitive p130 phosphorylation by CDK2. The persistence of phospho-p130 prevents DREAM complex assembly, enabling cell-cycle re-entry and tumor progression. Inhibitors of CDK2 can overcome p53 loss, leading to geroconversion and manifestation of senescence phenotypes. Complete inhibition of both CDK4/6 and CDK2 kinases appears to be necessary to facilitate long-term response across genomically diverse HR+ breast cancers.

Evidence Synthesis and Linkage for Modelling the Cost-Effectiveness of Diagnostic Tests: Preliminary Good Practice Recommendations

OBJECTIVES

To develop preliminary good practice recommendations for synthesising and linking evidence of treatment effectiveness when modelling the cost-effectiveness of diagnostic tests.

METHODS

We conducted a targeted review of guidance from key Health Technology Assessment (HTA) bodies to summarise current recommendations on synthesis and linkage of treatment effectiveness evidence within economic evaluations of diagnostic tests. We then focused on a specific case study, the cost-effectiveness of troponin for the diagnosis of myocardial infarction, and reviewed the approach taken to synthesise and link treatment effectiveness evidence in different modelling studies.

RESULTS

The Australian and UK HTA bodies provided advice for synthesising and linking treatment effectiveness in diagnostic models, acknowledging that linking test results to treatment options and their outcomes is common. Across all reviewed models for the case study, uniform test-directed treatment decision making was assumed, i.e., all those who tested positive were treated. Treatment outcome data from a variety of sources, including expert opinion, were utilised for linked clinical outcomes. Preliminary good practice recommendations for data identification, integration and description are proposed.

CONCLUSION

Modelling the cost-effectiveness of diagnostic tests poses unique challenges in linking evidence on test accuracy to treatment effectiveness data to understand how a test impacts patient outcomes and costs. Upfront consideration of how a test and its results will likely be incorporated into patient diagnostic pathways is key to exploring the optimal design of such models. We propose some preliminary good practice recommendations to improve the quality of cost-effectiveness evaluations of diagnostics tests going forward.

Molecular profiling of a real-world breast cancer cohort with genetically inferred ancestries reveals actionable tumor biology differences between European ancestry and African ancestry patient populations

BACKGROUND

Endocrine-resistant HR+/HER2- breast cancer (BC) and triple-negative BC (TNBC) are of interest for molecularly informed treatment due to their aggressive natures and limited treatment profiles. Patients of African Ancestry (AA) experience higher rates of TNBC and mortality than European Ancestry (EA) patients, despite lower overall BC incidence. Here, we compare the molecular landscapes of AA and EA patients with HR+/HER2- BC and TNBC in a real-world cohort to promote equity in precision oncology by illuminating the heterogeneity of potentially druggable genomic and transcriptomic pathways.

METHODS

De-identified records from patients with TNBC or HR+/HER2- BC in the Tempus Database were randomly selected (N = 5000), with most having stage IV disease. Mutations, gene expression, and transcriptional signatures were evaluated from next-generation sequencing data. Genetic ancestry was estimated from DNA-seq. Differences in mutational prevalence, gene expression, and transcriptional signatures between AA and EA were compared. EA patients were used as the reference population for log fold-changes (logFC) in expression.

RESULTS

After applying inclusion criteria, 3433 samples were evaluated (n = 623 AA and n = 2810 EA). Observed patterns of dysregulated pathways demonstrated significant heterogeneity among the two groups. Notably, PIK3CA mutations were significantly lower in AA HR+/HER2- tumors (AA = 34% vs. EA = 42%, P < 0.05) and the overall cohort (AA = 28% vs. EA = 37%, P = 2.08e-05). Conversely, KMT2C mutation was significantly more frequent in AA than EA TNBC (23% vs. 12%, P < 0.05) and HR+/HER2- (24% vs. 15%, P = 3e-03) tumors. Across all subtypes and stages, over 8000 genes were differentially expressed between the two ancestral groups including RPL10 (logFC = 2.26, P = 1.70e-162), HSPA1A (logFC = - 2.73, P = 2.43e-49), ATRX (logFC = - 1.93, P = 5.89e-83), and NUTM2F (logFC = 2.28, P = 3.22e-196). Ten differentially expressed gene sets were identified among stage IV HR+/HER2- tumors, of which four were considered relevant to BC treatment and were significantly enriched in EA: ERBB2_UP.V1_UP (P = 3.95e-06), LTE2_UP.V1_UP (P = 2.90e-05), HALLMARK_FATTY_ACID_METABOLISM (P = 0.0073), and HALLMARK_ANDROGEN_RESPONSE (P = 0.0074).

CONCLUSIONS

We observed significant differences in mutational spectra, gene expression, and relevant transcriptional signatures between patients with genetically determined African and European ancestries, particularly within the HR+/HER2- BC and TNBC subtypes. These findings could guide future development of treatment strategies by providing opportunities for biomarker-informed research and, ultimately, clinical decisions for precision oncology care in diverse populations.

Precision medicine: affording the successes of science

Science has made remarkable advances in understanding the molecular basis of disease, generating new and effective rationally-designed treatments at an accelerating rate. Ironically, the successes of science is creating a crisis in the affordability of equitable health care. The COVID-19 pandemic underscores both the value of science in health care, and the apparently inevitable tension between health and the economy. Drug development in ever-smaller target populations is a critical component of the rising costs of care. For structural and historical reasons, drug development is inefficient and poorly integrated across the public and private sectors. We postulate an alternative, integrated model in which governments and industry share the risks and benefits of drug development. The Australian government recently announced support for a AU$185 million innovative multi-stakeholder public-private partnership model for sustainable precision oncology, accelerating biomarker-dependent drug development through integrating clinical trials into the standard of care.

Validation of genomic and transcriptomic models of homologous recombination deficiency in a real-world pan-cancer cohort

Background

With the introduction of DNA-damaging therapies into standard of care cancer treatment, there is a growing need for predictive diagnostics assessing homologous recombination deficiency (HRD) status across tumor types. Following the strong clinical evidence for the utility of DNA-sequencing-based HRD testing in ovarian cancer, and growing evidence in breast cancer, we present analytical validation of the Tempus HRD-DNA test. We further developed, validated, and explored the Tempus HRD-RNA model, which uses gene expression data from 16,750 RNA-seq samples to predict HRD status from formalin-fixed paraffin-embedded tumor samples across numerous cancer types.

Methods

Genomic and transcriptomic profiling was performed using next-generation sequencing from Tempus xT, Tempus xO, Tempus xE, Tempus RS, and Tempus RS.v2 assays on 48,843 samples. Samples were labeled based on their BRCA1, BRCA2 and selected Homologous Recombination Repair pathway gene (CDK12, PALB2, RAD51B, RAD51C, RAD51D) mutational status to train and validate HRD-DNA, a genome-wide loss-of-heterozygosity biomarker, and HRD-RNA, a logistic regression model trained on gene expression.

Results

In a sample of 2058 breast and 1216 ovarian tumors, BRCA status was predicted by HRD-DNA with F1-scores of 0.98 and 0.96, respectively. Across an independent set of 1363 samples across solid tumor types, the HRD-RNA model was predictive of BRCA status in prostate, pancreatic, and non-small cell lung cancer, with F1-scores of 0.88, 0.69, and 0.62, respectively.

Conclusions

We predict HRD-positive patients across many cancer types and believe both HRD models may generalize to other mechanisms of HRD outside of BRCA loss. HRD-RNA complements DNA-based HRD detection methods, especially for indications with low prevalence of BRCA alterations.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09669-z.

Landscape of KRASG12C, Associated Genomic Alterations, and Interrelation With Immuno-Oncology Biomarkers in KRAS-Mutated Cancers

Promising single-agent activity from sotorasib and adagrasib in KRAS^G12C-mutant tumors has provided clinical evidence of effective KRAS signaling inhibition. However, comprehensive analysis of KRAS-variant prevalence, genomic alterations, and the relationship between KRAS and immuno-oncology biomarkers is lacking.