Triple-negative breast cancer (TNBC) is a subtype of breast tumor with unique characteristics in terms of clinical−pathological presentation, prognosis, and response to therapy. Epidemiological ...investigations focusing on the identification of risk factors involved in the onset and progression of TNBCs have identified unique demographic, anthropometric, and reproductive characteristics involved in the etiopathogenesis of this subtype of breast tumors. This systematic review and meta-analysis evaluates the association between TNBCs and obesity and menopause status. Eligible articles were identified through three databases and secondary reference analysis. The search was conducted from the first record to February 2012. Eleven original articles meeting a priori established inclusion criteria were incorporated in the quantitative analysis. Case−case and case–control comparisons were performed. In addition, a case–case comparison was conducted before and after stratification according to menopausal status. Based on the level of between-study heterogeneity, pooled odds ratio (OR) and 95 % confidence interval were calculated using fixed or random models. The case−case comparison showed a significant association between TNBC and obesity (OR: 1.20; 95 % CI: 1.03−1.40). These results were confirmed by the case–control comparison (OR: 1.24; 95 % CI: 1.06−1.46). Once stratification based on menopausal status was applied to the case–case analysis, significant results were observed only in the pre-menopausal group (OR: 1.43; 95 % CI: 1.23−1.65). According to this analysis, obese women are at a greater risk of presenting with a TNBC than non-obese women, and menopause status may be a mitigating factor. If validated, these findings should be taken into consideration for the development of targeted preventive programs.
Artificial intelligence and emerging data science techniques are being leveraged to interpret medical image scans. Traditional image analysis relies on visual interpretation by a trained radiologist, ...which is time-consuming and can, to some degree, be subjective. The development of reliable, automated diagnostic tools is a key goal of radiomics, a fast-growing research field which combines medical imaging with personalized medicine. Radiomic studies have demonstrated potential for accurate lung cancer diagnoses and prognostications. The practice of delineating the tumor region of interest, known as segmentation, is a key bottleneck in the development of generalized classification models. In this study, the incremental multiple resolution residual network (iMRRN), a publicly available and trained deep learning segmentation model, was applied to automatically segment CT images collected from 355 lung cancer patients included in the dataset "Lung-PET-CT-Dx", obtained from The Cancer Imaging Archive (TCIA), an open-access source for radiological images. We report a failure rate of 4.35% when using the iMRRN to segment tumor lesions within plain CT images in the lung cancer CT dataset. Seven classification algorithms were trained on the extracted radiomic features and tested for their ability to classify different lung cancer subtypes. Over-sampling was used to handle unbalanced data. Chi-square tests revealed the higher order texture features to be the most predictive when classifying lung cancers by subtype. The support vector machine showed the highest accuracy, 92.7% (0.97 AUC), when classifying three histological subtypes of lung cancer: adenocarcinoma, small cell carcinoma, and squamous cell carcinoma. The results demonstrate the potential of AI-based computer-aided diagnostic tools to automatically diagnose subtypes of lung cancer by coupling deep learning image segmentation with supervised classification. Our study demonstrated the integrated application of existing AI techniques in the non-invasive and effective diagnosis of lung cancer subtypes, and also shed light on several practical issues concerning the application of AI in biomedicine.
Diffuse gastric cancer (DGC) is a lethal malignancy lacking effective systemic therapy. Among the most provocative recent results in DGC has been that of highly recurrent missense mutations in the ...GTPase RHOA. The function of these mutations has remained unresolved. We demonstrate that RHOA
, the most common RHOA mutation in DGC, is a gain-of-function oncogenic mutant, and that expression of RHOA
with inactivation of the canonical tumor suppressor
induces metastatic DGC in a mouse model. Biochemically, RHOA
exhibits impaired GTP hydrolysis and enhances interaction with its effector ROCK.
mutation and
loss induce actin/cytoskeletal rearrangements and activity of focal adhesion kinase (FAK), which activates YAP-TAZ, PI3K-AKT, and β-catenin. RHOA
murine models were sensitive to FAK inhibition and to combined YAP and PI3K pathway blockade. These results, coupled with sensitivity to FAK inhibition in patient-derived DGC cell lines, nominate FAK as a novel target for these cancers. SIGNIFICANCE: The functional significance of recurrent RHOA mutations in DGC has remained unresolved. Through biochemical studies and mouse modeling of the hotspot RHOA
mutation, we establish that these mutations are activating, detail their effects upon cell signaling, and define how RHOA-mediated FAK activation imparts sensitivity to pharmacologic FAK inhibitors.
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Accumulating evidence supports a role of the PI3K-AKT pathway in the regulation of cell motility, invasion and metastasis. AKT activation is known to promote metastasis, however under certain ...circumstances, it also shows an inhibitory activity on metastatic processes, and the cause of such conflicting results is largely unclear. Here we found that AKT1 is an important regulator of metastasis and down-regulation of its activity is associated with increased metastatic potential of A549 cells. Inhibition of AKT1 enhanced migration and invasion in KRAS- or EGFR-mutant non-small cell lung cancer (NSCLC) cells. The allosteric AKT inhibitor MK-2206 promoted metastasis of KRAS-mutated A549 cells in vivo. We next identified that the phosphorylation of Myristoylated alanine-rich C-kinase substrate (MARCKS) and LAMC2 protein level were increased with AKT1 inhibition, and MARCKS or LAMC2 knockdown abrogated migration and invasion induced by AKT1 inhibition. This study unravels an anti-metastatic role of AKT1 in the NSCLC cells with KRAS or EGFR mutations, and establishes an AKT1-MARCKS-LAMC2 feedback loop in this regulation.
Population-based estimates of absolute risk of lung cancer recurrence, and of mortality rates after recurrence, can inform clinical management.
We evaluated prognostic factors for recurrences and ...survival in 2098 lung cancer case patients from the general population of Lombardy, Italy, from 2002 to 2005. We conducted survival analyses and estimated absolute risks separately for stage IA to IIIA surgically treated and stage IIIB to IV non-surgically treated patients.
Absolute risk of metastases exceeded that of local recurrence in every stage and cell type, highlighting the systemic threat of lung cancer. In stage I, the probability of dying within the first year after diagnosis was 2.7%, but it was 48.3% within first year after recurrence; in stage IV, the probabilities were 57.3% and 80.6%, respectively. Over half the patients died within one year of first metastasis. Although in stages IA to IB about one-third of patients had a recurrence, stage IIA patients had a recurrence risk (61.2%) similar to stage IIB (57.9%) and IIIA (62.8%) patients. Risk of brain metastases in stage IA to IIIA surgically treated non-small cell lung cancer patients increased with increasing tumor grade. Absolute risk of recurrence was virtually identical in adenocarcinoma and squamous cell carcinoma patients.
This population-based study provides clinically useful estimates of risks of lung cancer recurrence and mortality that are applicable to the general population. These data highlight the need for more effective adjuvant treatments overall and within specific subgroups. The estimated risks of various endpoints are useful for designing clinical trials, whose power depends on absolute numbers of events.
Little is known about the molecular signatures associated with specific metastatic sites in breast cancer. Using comprehensive multi-omic molecular profiling, we assessed whether alterations or ...activation of the PI3K-AKT-mTOR pathway is associated with specific sites of breast cancer metastasis.
Next-generation sequencing-based whole-exome sequencing was coupled with reverse-phase protein microarray (RPPA) functional signaling network analysis to explore the PI3K-AKT-mTOR axis in 32 pretreated breast cancer metastases. RPPA-based signaling data were further validated in an independent cohort of 154 metastatic lesions from breast cancer and 101 unmatched primary breast tumors. The proportion of cases with PI3K-AKT-mTOR genomic alterations or signaling network activation were compared between hepatic and nonhepatic lesions.
mutation and activation of AKT (S473) and p70S6K (T389) were detected more frequently among liver metastases than nonhepatic lesions (
< 0.01,
= 0.056, and
= 0.053, respectively). However,
mutations alone were insufficient in predicting protein activation (
= 0.32 and
= 0.19 for activated AKT and p70S6K, respectively). RPPA analysis of an independent cohort of 154 tumors confirmed the relationship between pathway activation and hepatic metastasis AKT (S473), mTOR (S2448), and 4EBP1 (S65);
< 0.01,
= 0.02, and
= 0.01, respectively. Similar results were also seen between liver metastases and primary breast tumors AKT (S473)
< 0.01, mTOR (S2448)
< 0.01, 4EBP1 (S65)
= 0.01. This signature was lost when primary tumors were compared with all metastatic sites combined.
Breast cancer patients with liver metastasis may represent a molecularly homogenized cohort with increased incidence of
mutations and activation of the PI3K-AKT-mTOR signaling network.
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Colorectal cancer (CRC) represents the fourth leading cause of cancer-related deaths. The heterogeneity of CRC identity limits the usage of cell lines to study this type of tumor because of the ...limited representation of multiple features of the original malignancy. Patient-derived colon organoids (PDCOs) are a promising 3D-cell model to study tumor identity for personalized medicine, although this approach still lacks detailed characterization regarding molecular stability during culturing conditions. Correlation analysis that considers genomic, transcriptomic, and proteomic data, as well as thawing, timing, and culturing conditions, is missing.
Through integrated multi-omics strategies, we characterized PDCOs under different growing and timing conditions, to define their ability to recapitulate the original tumor.
Whole Exome Sequencing allowed detecting temporal acquisition of somatic variants, in a patient-specific manner, having deleterious effects on driver genes CRC-associated. Moreover, the targeted NGS approach confirmed that organoids faithfully recapitulated patients' tumor tissue. Using RNA-seq experiments, we identified 5125 differentially expressed transcripts in tumor versus normal organoids at different time points, in which the PTEN pathway resulted of particular interest, as also confirmed by further phospho-proteomics analysis. Interestingly, we identified the PTEN c.806_817dup (NM_000314) mutation, which has never been reported previously and is predicted to be deleterious according to the American College of Medical Genetics and Genomics (ACMG) classification.
The crosstalk of genomic, transcriptomic and phosphoproteomic data allowed to observe that PDCOs recapitulate, at the molecular level, the tumor of origin, accumulating mutations over time that potentially mimic the evolution of the patient's tumor, underlining relevant potentialities of this 3D model.
Despite multiple possible oncogenic mutations in the proto-oncogene
, unique subsets of these mutations are detected in different cancer types. As
mutations occur early, if not being the initiating ...event, these mutational biases are ostensibly a product of how normal cells respond to the encoded oncoprotein. Oncogenic mutations can impact not only the level of active oncoprotein, but also engagement with proteins. To attempt to separate these two effects, we generated four novel Cre-inducible (LSL)
alleles in mice with the biochemically distinct G12D or Q61R mutations and encoded by native (nat) rare or common (com) codons to produce low or high protein levels. While there were similarities, each allele also induced a distinct transcriptional response shortly after activation in vivo. At one end of the spectrum, activating the
allele induced transcriptional hallmarks suggestive of an expansion of multipotent cells, while at the other end, activating the
allele led to hallmarks of hyperproliferation and oncogenic stress. Evidence suggests that these changes may be a product of signaling differences due to increased protein expression as well as the specific mutation. To determine the impact of these distinct responses on RAS mutational patterning in vivo, all four alleles were globally activated, revealing that hematolymphopoietic lesions were permissive to the level of active oncoprotein, squamous tumors were permissive to the G12D mutant, while carcinomas were permissive to both these features. We suggest that different KRAS mutations impart unique signaling properties that are preferentially capable of inducing tumor initiation in a distinct cell-specific manner.
Implementing targeted drug therapy in radio-oncologic treatment regimens has greatly improved the outcome of cancer patients. However, the efficacy of molecular targeted drugs such as inhibitory ...antibodies or small molecule inhibitors essentially depends on target expression and activity, which both can change during the course of treatment. Radiotherapy has previously been shown to activate prosurvival pathways, which can help tumor cells to adapt and thereby survive treatment. Therefore, we aimed to identify changes in signaling induced by radiation and evaluate the potential of targeting these changes with small molecules to increase the therapeutic efficacy on cancer cell survival. Analysis of "The Cancer Genome Atlas" database disclosed a significant overexpression of
, and
genes in human prostate cancer samples compared with normal prostate gland tissue. Multifractionated radiation of three-dimensional-cultured prostate cancer cell lines with a dose of 2 Gy/day as a clinically relevant schedule resulted in an increased protein phosphorylation and enhanced protein-protein interaction between AKT and mTOR, whereas gene expression of
, and related kinases was not altered by radiation. Similar results were found in a xenograft model of prostate cancer. Pharmacologic inhibition of mTOR/AKT signaling after activation by multifractionated radiation was more effective than treatment prior to radiotherapy. Taken together, our findings provide a proof-of-concept that targeting signaling molecules after activation by radiotherapy may be a novel and promising treatment strategy for cancers treated with multifractionated radiation regimens such as prostate cancer to increase the sensitivity of tumor cells to molecular targeted drugs.
Targeting of the HER2 protein in human breast cancer represents a major advance in oncology but relies on measurements of total HER2 protein and not HER2 signaling network activation. We used ...reverse-phase protein microarrays (RPMA) to measure total and phosphorylated HER2 in the context of HER family signaling to understand correlations between phosphorylated and total levels of HER2 and downstream signaling activity.
Three independent study sets, comprising a total of 415 individual patient samples from flash-frozen core biopsy samples and formalin-fixed and paraffin-embedded (FFPE) surgical and core samples, were analyzed via RPMA. The phosphorylation and total levels of the HER receptor family proteins and downstream signaling molecules were measured in laser capture microdissected (LCM) enriched tumor epithelium from 127 frozen pretreatment core biopsy samples and whole-tissue lysates from 288 FFPE samples and these results were compared with FISH and immunohistochemistry (IHC).
RPMA measurements of total HER2 were highly concordant (>90% all sets) with FISH and/or IHC data, as was phosphorylation of HER2 in the FISH/IHC(+) population. Phosphorylation analysis of HER family signaling identified HER2 activation in some FISH/IHC(-) tumors and, identical to that seen with FISH/IHC(+) tumors, the HER2 activation was concordant with EGF receptor (EGFR) and HER3 phosphorylation and downstream signaling endpoint activation.
Molecular profiling of HER2 signaling of a large cohort of human breast cancer specimens using a quantitative and sensitive functional pathway activation mapping technique reveals IHC(-)/FISH(-)/pHER2(+) tumors with HER2 pathway activation independent of total HER2 levels and functional signaling through HER3 and EGFR.
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