Chromosomal INstability (CIN), a hallmark of cancer, refers to cells with an increased rate of gain or loss of whole chromosomes or chromosome parts. CIN is linked to the progression of tumors with poor clinical outcomes such as drug resistance. CIN can give tumors the diversity to resist therapy, but it comes at the cost of significant stress to tumor cells. To tolerate this, cancer cells must modify their energy use to provide adaptation against genetic changes as well as to promote their survival and growth. In this study, we have demonstrated that CIN induction causes sensitivity to metabolic stress. We show that mild metabolic disruption that does not affect normal cells, can lead to high levels of oxidative stress and subsequent cell death in CIN cells because they are already managing elevated stress levels. Altered metabolism is a differential characteristic of cancer cells, so our identification of key regulators that can exploit these changes to cause cell death may provide cancer-specific potential drug targets, especially for advanced cancers that exhibit CIN.

Valeriana jatamansi is an indigenous medicinal plant used in the treatment of a number of diseases. In the present study, chemical composition of the essential oil was determined by GC-MS. Seven major components were identified in Valeriana jatamansi essential oil, namely, β-vatirenene, β-patchoulene, dehydroaromadendrene, β-gurjunene, patchoulic alcohol, β-guaiene, and α-muurolene. Methanolic, aqueous, and chloroform extracts of Valeriana jatamansi roots were also prepared and analyzed for their polyphenols and flavonoid content. Antioxidant activity of essential oil and different extracts of Valeriana jatamansi roots was determined by DPPH radical scavenging and chelation power assay. A linear correlation has been obtained by comparing the antioxidant activity and polyphenols and flavonoid content of the extracts. Results indicated that antioxidant activity of methanolic extract could be attributed to the presence of rich amount of polyphenols and flavonoid. Essential oil of Valeriana jatamansi roots showed moderate antioxidant activity.

The production of reactive oxygen species is a normal part of cell physiology, but many internal and external stimuli are able to trigger the production of excess levels of oxidants that are potentially damaging. The threat of oxidative damage is particularly significant to DNA, as damaged bases can interfere with replication to generate lasting mutations. Signalling through the JNK pathway is a key cellular response to oxidative damage. Depending on the intensity and duration of the damage signal, JNK signalling can lead to distinct alternative responses including DNA repair, anti-oxidant production or cell death. These responses are highly relevant to cancer therapy, as tumours are often under oxidative stress that produces elevated JNK levels and therapy often involves inducing DNA damage with the intention of driving cell death. In this review we examine the causes and consequences of JNK activation that relate to oxidative DNA damage, with a focus on the potential therapeutic implications.

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Top-Down Proteomics (TDP) is an emerging proteomics protocol that involves identification, characterization, and quantitation of intact proteins using high-resolution mass spectrometry. TDP has an edge over other proteomics protocols in that it allows for: (i) accurate measurement of intact protein mass, (ii) high sequence coverage, and (iii) enhanced identification of post-translational modifications (PTMs). However, the complexity of TDP spectra poses a significant impediment to protein search and PTM characterization. Furthermore, limited software support is currently available in the form of search algorithms and pipelines. To address this need, we propose ‘SPECTRUM’, an open-architecture and open-source toolbox for TDP data analysis. Its salient features include: (i) MS2-based intact protein mass tuning, (ii) de novo peptide sequence tag analysis, (iii) propensity-driven PTM characterization, (iv) blind PTM search, (v) spectral comparison, (vi) identification of truncated proteins, (vii) multifactorial coefficient-weighted scoring, and (viii) intuitive graphical user interfaces to access the aforementioned functionalities and visualization of results. We have validated SPECTRUM using published datasets and benchmarked it against salient TDP tools. SPECTRUM provides significantly enhanced protein identification rates (91% to 177%) over its contemporaries. SPECTRUM has been implemented in MATLAB, and is freely available along with its source code and documentation at https://github.com/BIRL/SPECTRUM/ .