Caveolin-1 Mediates Inflammatory Breast Cancer Cell Invasion via the Akt1 Pathway and RhoC GTPase

Applying image features of proximal paracancerous tissues in predicting prognosis of patients with hepatocellular carcinoma

BACKGROUND

Most of the methods using digital pathological image for predicting Hepatocellular carcinoma (HCC) prognosis have not considered paracancerous tissue microenvironment (PTME), which are potentially important for tumour initiation and metastasis. This study aimed to identify roles of image features of PTME in predicting prognosis and tumour recurrence of HCC patients.

METHODS

We collected whole slide images (WSIs) of 146 HCC patients from Sun Yat-sen Memorial Hospital (SYSM dataset). For each WSI, five types of regions of interests (ROIs) in PTME and tumours were manually annotated. These ROIs were used to construct a Lasso Cox survival model for predicting the prognosis of HCC patients. To make the model broadly useful, we established a deep learning method to automatically segment WSIs, and further used it to construct a prognosis prediction model. This model was tested by the samples of 225 HCC patients from the Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC).

RESULTS

In predicting prognosis of the HCC patients, using the image features of manually annotated ROIs in PTME achieved C-index 0.668 in the SYSM testing dataset, which is higher than the C-index 0.648 reached by the model only using image features of tumours. Integrating ROIs of PTME and tumours achieved C-index 0.693 in the SYSM testing dataset. The model using automatically segmented ROIs of PTME and tumours achieved C-index of 0.665 (95% CI: 0.556-0.774) in the TCGA-LIHC samples, which is better than the widely used methods, WSISA (0.567), DeepGraphSurv (0.593), and SeTranSurv (0.642). Finally, we found the Texture SumAverage Skew HV on immune cell infiltration and Texture related features on desmoplastic reaction are the most important features of PTME in predicting HCC prognosis. We additionally used the model in prediction HCC recurrence for patients from SYSM-training, SYSM-testing, and TCGA-LIHC datasets, indicating the important roles of PTME in the prediction.

CONCLUSIONS

Our results indicate image features of PTME is critical for improving the prognosis prediction of HCC. Moreover, the image features related with immune cell infiltration and desmoplastic reaction of PTME are the most important factors associated with prognosis of HCC.

iTRAQ proteomics of sentinel lymph nodes for identification of extracellular matrix proteins to flag metastasis in early breast cancer

Patients with early breast cancer are affected by metastasis to axillary lymph nodes. Metastasis to these nodes is crucial for staging and quality of surgery. Sentinel Lymph Node Biopsy that is currently used to assess lymph node metastasis is not effective. This necessitates identification of biomarkers that can flag metastasis. Early stage breast cancer patients were recruited. Surgical resection of breast was followed by identification of sentinel lymph nodes. Fresh frozen section biopsy was used to assign metastatic and non-metastatic sentinel lymph nodes. Discovery phase included iTRAQ proteomics coupled with mass spectrometric analysis to identify differentially expressed proteins. Data is available via ProteomeXchange with identifier PXD027668. Validation was done by bioinformatic analysis and ELISA. There were 2398 unique protein groups and 109 differentially expressed proteins comparing metastatic and non-metastatic lymph nodes. Forty nine proteins were up-regulated, and sixty proteins that were down regulated in metastatic group. Bioinformatic analysis showed ECM-receptor interaction pathways to be implicated in lymph node metastasis. ELISA confirmed up-regulation of ECM proteins in metastatic lymph nodes. ECM proteins have requisite parameters to be developed as a diagnostic tool to assess status of sentinel lymph nodes to guide surgical intervention in early breast cancer.

RhoC: a fascinating journey from a cytoskeletal organizer to a Cancer stem cell therapeutic target

Tumor heterogeneity results in differential response to therapy due to the existence of plastic tumor cells, called cancer stem cells (CSCs), which exhibit the property of resistance to therapy, invasion and metastasis. These cells have a distinct, signaling network active at every stage of progression. It is difficult to envisage that the CSCs will have a unique set of signaling pathways regulating every stage of disease progression. Rather, it would be easier to believe that a single pivotal pathway having significant contribution at every stage, which can further turn on a battery of signaling mechanisms specific to that stage, would be instrumental in regulating the signaling network, enabling easy transition from one state to another. In this context, we discuss the role of RhoC which has contributed to several phenotypes during tumor progression.

RhoC (Ras homolog gene family member C) has been widely reported to regulate actin organization. It has been shown to impact the motility of cancer cells, resultantly affecting invasion and metastasis, and has contributed to carcinoma progression of the breast, pancreas, lung, ovaries and cervix, among several others. The most interesting finding has been its indispensable role in metastasis. Also, it has the ability to modulate various other phenotypes like angiogenesis, motility, invasion, metastasis, and anoikis resistance. These observations suggest that RhoC imparts the plasticity required by tumor cells to exhibit such diverse functions based on microenvironmental cues. This was further confirmed by recent reports which show that it regulates cancer stem cells in breast, ovary and head and neck cancers. Studies also suggest that the inhibition of RhoC results in abolition of advanced tumor phenotypes.

Our review throws light on how RhoC, which is capable of modulating various phenotypes may be the apt core signaling candidate regulating disease progression. Additionally, mice studies show that RhoC is not essential for embryogenesis, giving scope for its development as a possible therapeutic target. This review thus stresses on the need to understand the protein and its functioning in greater detail to enable its development as a stem cell marker and a possible therapeutic target.