Hypoxia is a common feature of solid tumors and is associated with cancer progression. We investigated the effect of hypoxia followed by reoxygenation on the phenotypic behavior of two breast cancer cell lines, MCF-7 and MDA-MB-231. MCF-7 and MDA-MB-231 cells were exposed to controlled hypoxia (1

Supplementary Table 3 shows the Hallmarks, Canonical Pathways, and Gene Ontologies with FDR q-value <0.05 enriched in MSigDB for significantly de-regulated genes in each comparison (AvB, BvC and AvC) in individual patient time-series analysis for breast cancer.

Supplementary Figure 4 shows the ClueGO Gene Ontology analysis for 85 genes de-regulated in both patient-specific analysis and replicate analysis for breast cancer RNA-Seq data.

Supplementary Table 8 shows the Genes included in qPCR validation.

Abstract Surgery exposes tumor tissue to severe hypoxia and mechanical stress leading to rapid gene expression changes in the tumor and its microenvironment, which remain poorly characterized. We biopsied tumor and adjacent normal tissues from patients with breast (n = 81) and head/neck squamous cancers (HNSC; n = 10) at the beginning (A), during (B), and end of surgery (C). Tumor/normal RNA from 46/81 patients with breast cancer was subjected to mRNA-Seq using Illumina short-read technology, and from nine patients with HNSC to whole-transcriptome microarray with Illumina BeadArray. Pathways and genes involved in 7 of 10 known cancer hallmarks, namely, tumor-promoting inflammation (TNF-A, NFK-B, IL18 pathways), activation of invasion and migration (various extracellular matrix–related pathways, cell migration), sustained proliferative signaling (K-Ras Signaling), evasion of growth suppressors (P53 signaling, regulation of cell death), deregulating cellular energetics (response to lipid, secreted factors, and adipogenesis), inducing angiogenesis (hypoxia signaling, myogenesis), and avoiding immune destruction (CTLA4 and PDL1) were significantly deregulated during surgical resection (time points A vs. B vs. C). These findings were validated using NanoString assays in independent pre/intra/post-operative breast cancer samples from 48 patients. In a comparison of gene expression data from biopsy (analogous to time point A) with surgical resection samples (analogous to time point C) from The Cancer Genome Atlas study, the top deregulated genes were the same as identified in our analysis, in five of the seven studied cancer types. This study suggests that surgical extirpation deregulates the hallmarks of cancer in primary tumors and adjacent normal tissue across different cancers. Implications: Surgery deregulates hallmarks of cancer in human tissue.

Supplementary Table 6 shows the Clinical characteristics of CA HNSCC patients. All staging was done using AJCC 7th edition of the Oral cavity cancer staging systems.

Supplementary Table 11 shows Overlap of genes de-regulated from our study with genes known to be de-regulated due to hypoxia in literature.

Supplementary Materials and Methods

Supplementary Figure 3 summarises differential genes identified via class comparisons AvB, BvC and AvC in replicate analysis of breast cancer RNA-Seq data.

Supplementary Table 4 shows Genes deregulated in replicate analysis for breast cancer patients with their log-fold change values.

Supplementary Table 7 shows Genes de-regulated between various time-points during surgery in HNSCC Microarray data.

Supplementary Table 5 shows the GO terms for 85 significantly de-regulated genes common to the individual patient time-series analysis and replicative analysis in Breast Cancer Patients.

Supplementary Figure shows Venn diagram representation & heatmap for time-series microarray-based gene expression comparison between tumor-adjacent normal tissue at the start of surgery & tumor tissue obtained at various timepoints in head & neck cancer patients.

Supplementary Table 9 shows the Genes significantly de-regulated at three timepoints of surgery in breast cancer NanoString nCounter targeted assays.

Supplementary Figure 2 shows unsupervised clustering of Breast Cancer patients based on genome-wide expression counts.

Supplementary Figure 1 shows the effect of various transformation methods on RNA-Seq data from breast cancer patients.

Supplementary Table 10 shows Genes de-regulated between normal at start of surgery and tumour tissues at differing points of surgery in HNSCC Microarray data.

Supplementary Table 2 shows the 4854 unique genes found to be de-regulated in any one comparison across all comparisons for AvB, BvC and AvC in for breast cancer individual patient specific RNA-Seq analysis.

Supplementary Table S1; Supplementary Figures S1-S2. Supplementary Table 1. A) IC50 value of P7170 in pan-PI3K. B) Kinase inhibition data (ProQinase) of P7170 at 250 nM and 1. 5 μM.C) Kinase inhibition profile (KINOMEscan; 320 kinases) of P7170. D) IC50 values of selected kinases on treatment with P7170. Supplementary Figure S1. The growth response curves on treatment of P7170 on various patient-derived cancer cell lines. Supplementary Figure S2. P7170 induces autophagy in A2780 (A) and HCT116 (B) cells.