The current clinical value of genomic instability

Synergy between imputed genetic pathway and clinical information for predicting recurrence in early stage non-small cell lung cancer

OBJECTIVE

Lung cancer exhibits unpredictable recurrence in low-stage tumors and variable responses to different therapeutic interventions. Predicting relapse in early-stage lung cancer can facilitate precision medicine and improve patient survivability. While existing machine learning models rely on clinical data, incorporating genomic information could enhance their efficiency. This study aims to impute and integrate specific types of genomic data with clinical data to improve the accuracy of machine learning models for predicting relapse in early-stage, non-small cell lung cancer patients.

METHODS

The study utilized a publicly available TCGA lung cancer cohort and imputed genetic pathway scores into the Spanish Lung Cancer Group (SLCG) data, specifically in 1348 early-stage patients. Initially, tumor recurrence was predicted without imputed pathway scores. Subsequently, the SLCG data were augmented with pathway scores imputed from TCGA. The integrative approach aimed to enhance relapse risk prediction performance.

RESULTS

The integrative approach achieved improved relapse risk prediction with the following evaluation metrics: an area under the precision-recall curve (PR-AUC) score of 0.75, an area under the ROC (ROC-AUC) score of 0.80, an F1 score of 0.61, and a Precision of 0.80. The prediction explanation model SHAP (SHapley Additive exPlanations) was employed to explain the machine learning model's predictions.

CONCLUSION

We conclude that our explainable predictive model is a promising tool for oncologists that addresses an unmet clinical need of post-treatment patient stratification based on the relapse risk while also improving the predictive power by incorporating proxy genomic data not available for specific patients.

The Role of Chromosomal Instability in Cancer and Therapeutic Responses

Cancer is one of the leading causes of death, and despite increased research in recent years, control of advanced-stage disease and optimal therapeutic responses remain elusive. Recent technological improvements have increased our understanding of human cancer as a heterogeneous disease. For instance, four hallmarks of cancer have recently been included, which in addition to being involved in cancer development, could be involved in therapeutic responses and resistance. One of these hallmarks is chromosome instability (CIN), a source of genetic variation in either altered chromosome number or structure. CIN has become a hot topic in recent years, not only for its implications in cancer diagnostics and prognostics, but also for its role in therapeutic responses. Chromosomal alterations are mainly used to determine genetic heterogeneity in tumors, but CIN could also reveal treatment efficacy, as many therapies are based on increasing CIN, which causes aberrant cells to undergo apoptosis. However, it should be noted that contradictory findings on the implications of CIN for the therapeutic response have been reported, with some studies associating high CIN with a better therapeutic response and others associating it with therapeutic resistance. Considering these observations, it is necessary to increase our understanding of the role CIN plays not only in tumor development, but also in therapeutic responses. This review focuses on recent studies that suggest possible mechanisms and consequences of CIN in different disease types, with a primary focus on cancer outcomes and therapeutic responses.

The Landscape of Whole-genome Alterations and Pathologic Features in Genitourinary Malignancies: An Analysis of the Cancer Genome Atlas

BACKGROUND

The accumulation of somatic genetic alterations drives carcinogenesis. Little is known, however, about how the level of genetic alteration across an entire cancer genome affects tumor grade, stage or survival.

OBJECTIVE

To investigate the influence of somatic mutation count (MC) and copy number variation (CNV) on pathologic and oncologic outcomes in patients with genitourinary malignancies in The Cancer Genome Atlas (TCGA).

DESIGN, SETTING, AND PARTICIPANTS

TCGA data sets for adrenocortical carcinoma (ACC), bladder urothelial carcinoma (BLCA), chromophobe renal cell carcinoma (RCC; KICH), clear cell RCC (KIRC), papillary RCC (KIRP), pheochromocytoma and paraganglioma (PCPG), prostate adenocarcinoma (PRAD), and testis germ cell tumor (TGCT) were accessed via cBioportal.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Median MC and CNV were compared among and within each tumor type. Patients were stratified by grade and stage, and differences in MC and CNV were compared. Correlation of MC and CNV with overall survival (OS) and recurrence-free survival (RFS) was analyzed when these data were available.

RESULTS AND LIMITATIONS

Among the tumor types analyzed, BLCA had the highest MC at 167, followed by ACC (89), KIRP (71), TGCT (55), KIRC (45), PRAD (34), PCPG (14), and KICH (12). The tumor type with the highest fraction of the genome with CNV was KICH (0.94), followed by ACC (0.58), TGCT (0.41), BLCA (0.29), KIRP (0.15), PCPG (0.13), KIRC (0.12), and PRAD (0.06). MC was associated with higher T stage in ACC, N stage in KIRC, M stage in ACC, grade in BLCA, and primary Gleason score in PRAD, and was associated with OS and RFS in KICH. CNV was associated with higher N stage in PRAD, grade in KIRC, and Gleason grade in PRAD. In addition, higher CNV was independently associated with inferior RFS for KIRC, as well as inferior OS and RFS for KIRP.

CONCLUSIONS

MC and CNV vary greatly among tumor types.

PATIENT SUMMARY

Cancers with higher levels of genomic alterations are associated with worse pathologic features and survival. The degree of genomic alterations could serve as a useful marker of disease aggressiveness.

Chromosomal instability as a prognostic marker in cervical cancer

Background

Cervical cancer is the third most common cancer in women globally, and despite treatment, distant metastasis and nodal recurrence will still develop in approximately 30% of patients. The ability to predict which patients are likely to experience distant relapse would allow clinicians to better tailor treatment. Previous studies have investigated the role of chromosomal instability (CIN) in cancer, which can promote tumour initiation and growth; a hallmark of human malignancies. In this study, we sought to examine the published CIN70 gene signature in a cohort of cervical cancer patients treated at the Princess Margaret (PM) Cancer Centre and an independent cohort of The Cancer Genome Atlas (TCGA) cervical cancer patients, to determine if this CIN signature associated with patient outcome.

Methods

Cervical cancer samples were collected from 79 patients, treated between 2000–2007 at the PM, prior to undergoing curative chemo-radiation. Total RNA was extracted from each patient sample and analyzed using the GeneChip Human Genome U133 Plus 2.0 array (Affymetrix).

Results

High CIN70 scores were significantly related to increased chromosomal alterations in TCGA cervical cancer patients, including a higher percentage of genome altered and a higher number of copy number alterations. In addition, this same CIN70 signature was shown to be predictive of para-aortic nodal relapse in the PM Cancer Centre cohort.

Conclusions

These findings demonstrate that chromosomal instability plays an important role in cervical cancer, and is significantly associated with patient outcome. For the first time, this CIN70 gene signature provided prognostic value for patients with cervical cancer.

Emerging technologies in extracellular vesicle-based molecular diagnostics

Extracellular vesicles (EVs), including exosomes and microvesicles, have been shown to carry a variety of biomacromolecules including mRNA, microRNA and other non-coding RNAs. Within the past 5 years, EVs have emerged as a promising minimally invasive novel source of material for molecular diagnostics. Although EVs can be easily identified and collected from biological fluids, further research and proper validation is needed in order for them to be useful in the clinical setting. In addition, innovative and more efficient means of nucleic acid profiling are needed to facilitate investigations into the cellular and molecular mechanisms of EV function and to establish their potential as useful clinical biomarkers and therapeutic tools. In this article, we provide an overview of recent technological improvements in both upstream EV isolation and downstream analytical technologies, including digital PCR and next generation sequencing, highlighting future prospects for EV-based molecular diagnostics.

Genomic instability in patients with non-small cell lung cancer assessed by the arbitrarily primed polymerase chain reaction

In the present study, we used DNA profiling to measure genomic instability in 22 patients with non-small cell lung cancer (NSCLC). Genomic instability was correlated with gender, the age of the patients at the time of diagnosis, the NSCLC subtype, histological grade and stage of the tumor, necrosis presence in the tumor and lymph node invasion. Genomic instability was significantly higher in patients older than 50 and those with adenocarcinoma compared to squamous-cell carcinoma. Most importantly, genomic instability significantly decreased as the tumor grade increased. Extensive genomic instability in the early carcinogenesis could be the prerequisite for NSCLC progression.

MLH1 -93G>A promoter polymorphism and the risk of microsatellite-unstable colorectal cancer

BACKGROUND

Although up to 30% of patients with colorectal cancer have a positive family history of colorectal neoplasia, few colorectal cancers can be explained by mutations in high-penetrance genes. We investigated whether polymorphisms in DNA mismatch repair genes are associated with the risk of colorectal cancer.

METHODS

We genotyped 929 case patients and 1098 control subjects from Ontario and 430 case patients and 275 control subjects from Newfoundland and Labrador for five polymorphisms in the mismatch repair genes MLH1 and MSH2 with the fluorogenic 5' nuclease assay. Tumor microsatellite instability (MSI) was determined with a polymerase chain reaction-based method; MSI status was assigned as high (MSI-H, > or = 30% unstable markers among all markers tested), low (MSI-L, <30% markers unstable), or stable (MSS, no unstable markers). We used unconditional logistic regression to evaluate the association between each polymorphism and colorectal cancer after adjusting for age and sex. The associations between polymorphisms and tumor clinicopathologic features were evaluated with a Pearson's chi-square or Fisher's exact test. All statistical tests were two-sided.

RESULTS

We observed strong associations between the MLH1 -93G>A polymorphism and MSI-H tumors among case patients from Ontario (P = .001) and Newfoundland (P = .003). When compared with the control populations, homozygosity for the MLH1 -93G>A variant allele was associated with MSI-H tumors among case patients in Ontario (adjusted odds ratio [OR] = 3.23, 95% confidence interval [CI] = 1.65 to 6.30) and in Newfoundland (OR = 8.88, 95% CI = 2.33 to 33.9), as was heterozygosity among case patients in Ontario (OR = 1.84, 95% CI = 1.20 to 2.83) and in Newfoundland (OR = 2.56, 95% CI = 1.14 to 5.75). Genotype frequencies were similar among case patients with MSS and MSI-L tumors and control subjects, and the majority of homozygous variant carriers had MSS tumors. Among case patients from Ontario, an association between the MLH1 -93G>A polymorphism and a strong family history of colorectal cancer (for Amsterdam criteria I and II, P = .004 and P = .02, respectively) was observed.

CONCLUSION

In two patient populations, the MLH1 -93G>A polymorphism was associated with an increased risk of MSI-H colorectal cancer.

A signature of chromosomal instability inferred from gene expression profiles predicts clinical outcome in multiple human cancers

We developed a computational method to characterize aneuploidy in tumor samples based on coordinated aberrations in expression of genes localized to each chromosomal region. We summarized the total level of chromosomal aberration in a given tumor in a univariate measure termed total functional aneuploidy. We identified a signature of chromosomal instability from specific genes whose expression was consistently correlated with total functional aneuploidy in several cancer types. Net overexpression of this signature was predictive of poor clinical outcome in 12 cancer data sets representing six cancer types. Also, the signature of chromosomal instability was higher in metastasis samples than in primary tumors and was able to stratify grade 1 and grade 2 breast tumors according to clinical outcome. These results provide a means to assess the potential role of chromosomal instability in determining malignant potential over a broad range of tumors.

Biological diagnosis for neuroblastoma using the combination of highly sensitive analysis of prognostic factors

BACKGROUND/PURPOSE

To select the optimal treatment according to the degree of malignancy of neuroblastoma, it is essential to accurately and rapidly identify any genetic abnormalities associated with the prognosis. This study aims to assess the correlation between the combination of prognostic factors and the biologic findings of neuroblastoma using a highly sensitive analysis of prognostic factors.

METHODS

In 44 neuroblastoma primary samples, we determined the gene dosages of MYCN and Survivin (as the target of 17q gain) and the expression levels of MYCN, Survivin, and BIN1 using highly sensitive analysis (the quantitative polymerase chain reaction method); furthermore, we assessed the correlation between the combination of their prognostic factors and the biology of neuroblastoma.

RESULTS

The gene dosage of MYCN or Survivin was significantly associated with all known prognostic factors. The expression level of MYCN or Survivin was not significantly associated with any prognostic factors, whereas the expression level of BIN1 was significantly associated with 5 of 6 prognostic factors. Regarding the combination of MYCN amplification and 17q gain (the gene dosage of Survivin), and the low expression of BIN1, the rates of advanced stages (stage III or IV) were 100% for the cases with 3 factors, 63% for the cases with 2 factors, 42% for the cases with 1 factor, and 0% for the cases with null factor. Furthermore, the survival rates were 20% for the cases with 3 factors, 50% for the cases with 2 factors, 100% for the cases with 1 factor, and 100% for the cases with null factor.

CONCLUSION

The combination of gene dosages of MYCN and Survivin and the expression level of BIN1 using the quantitative polymerase chain reaction method was significantly correlated with the clinical stage and the patients' outcome. This combination of biologic factors may enhance the accuracy to the conventional criteria, but this would have to be shown in a much larger study that is adequately powered to detect such an advantage.