Collective heterogeneity of mitochondrial potential in contact inhibition of proliferation.

In the epithelium, cell density and cell proliferation are closely connected to each other through contact inhibition of proliferation (CIP). Depending on cell density, CIP proceeds through three distinct stages: the free-growing stage at low density, the pre-epithelial transition stage at medium density, and the post-epithelial transition stage at high density. Previous studies have elucidated how cell morphology, motion, and mechanics vary in these stages. However, it remains unknown whether cellular metabolism also has a density-dependent behavior. By measuring the mitochondrial membrane potential at different cell densities, here we reveal a heterogeneous landscape of metabolism in the epithelium, which appears qualitatively distinct in three stages of CIP and did not follow the trend of other CIP-associated parameters, which increases or decreases monotonically with increasing cell density. Importantly, epithelial cells established a collective metabolic heterogeneity exclusively in the pre-epithelial transition stage, where the multicellular clusters of high- and low-potential cells emerged. However, in the post-epithelial transition stage, the metabolic potential field became relatively homogeneous. Next, to study the underlying dynamics, we constructed a system biology model, which predicted the role of cell proliferation in metabolic potential toward establishing collective heterogeneity. Further experiments indeed revealed that the metabolic pattern spatially correlated with the proliferation capacity of cells, as measured by the nuclear localization of a pro-proliferation protein, YAP. Finally, experiments perturbing the actomyosin contractility revealed that, while metabolic heterogeneity was maintained in the absence of actomyosin contractility, its ab initio emergence depended on the latter. Taken together, our results revealed a density-dependent collective heterogeneity in the metabolic field of a pre-epithelial transition-stage epithelial monolayer, which may have significant implications for epithelial form and function.

Coupled mutual inhibition and mutual activation motifs as tools for cell-fate control.

Multistability is central to biological systems as it plays a crucial role in adaptation, evolvability, and differentiation. The presence of positive feedback loops can enable multistability. The simplest of such feedback loops are a) a mutual inhibition loop (MI), b) a mutual activation loop (MA), and c) self-activation, all three of them known to give rise to bistability. However, the characteristic differences in the bistability exhibited by these motifs are relatively less understood. Here, we use dynamical simulations across a large ensemble of parameter sets and initial conditions to study the bistability characteristics of these motifs. Furthermore, we investigate the utility of these motifs for achieving coordinated expression through cyclic and parallel coupling amongst them. Our analysis revealed that MI-based architectures offer discrete and robust control over gene expression, multistability, and coordinated expression among multiple genes, as compared to MA-based architectures. We then devised a combination of MI and MA architectures to improve coordination and multistability. Such designs help improve our understanding of the control structures involved in robust cell-fate decisions and provide a way to achieve controlled decision-making in synthetic systems.

Network topology metrics explaining enrichment of hybrid epithelial/mesenchymal phenotypes in metastasis.

Epithelial to Mesenchymal Transition (EMT) and its reverse-Mesenchymal to Epithelial Transition (MET) are hallmarks of metastasis. Cancer cells use this reversible cellular programming to switch among Epithelial (E), Mesenchymal (M), and hybrid Epithelial/Mesenchymal (hybrid E/M) state(s) and seed tumors at distant sites. Hybrid E/M cells are often more aggressive and metastatic than the "pure" E and M cells. Thus, identifying mechanisms to inhibit hybrid E/M cells can be promising in curtailing metastasis. While multiple gene regulatory networks (GRNs) based mathematical models for EMT/MET have been developed recently, identifying topological signatures enriching hybrid E/M phenotypes remains to be done. Here, we investigate the dynamics of 13 different GRNs and report an interesting association between "hybridness" and the number of negative/positive feedback loops across the networks. While networks having more negative feedback loops favor hybrid phenotype(s), networks having more positive feedback loops (PFLs) or many HiLoops-specific combinations of PFLs, support terminal (E and M) phenotypes. We also establish a connection between "hybridness" and network-frustration by showing that hybrid phenotypes likely result from non-reinforcing interactions among network nodes (genes) and therefore tend to be more frustrated (less stable). Our analysis, thus, identifies network topology-based signatures that can give rise to, as well as prevent, the emergence of hybrid E/M phenotype in GRNs underlying EMP. Our results can have implications in terms of targeting specific interactions in GRNs as a potent way to restrict switching to the hybrid E/M phenotype(s) to curtail metastasis.

A novel pictorial smile chart: Reliability and validity.

INTRODUCTION: Smile analysis provides data on the positive and negative elements of a patient's smile. We aimed to develop a simple pictorial chart to record relevant parameters of the smile analysis in a single diagram and to investigate the reliability and validity of this chart. METHODS: A panel of 5 orthodontists developed a graphical chart, which was reviewed by 12 orthodontists and 10 orthodontic residents. The chart comprises facial, perioral, and dentogingival zones analyzing 8 continuous and 4 discrete variables. The chart was tested on frontal smiling photographs of 40 young (aged 15-18 years) and 40 old (aged 50-55 years) patients. All measurements were performed twice with an interval of 2 weeks by 2 observers. RESULTS: Pearson's correlation coefficients for observers and age groups varied from 0.860 to 1.000 and between observers from 0.753 to 0.999. Minor significant mean differences were found between the first and second observations, which were not clinically relevant. The kappa scores for the dichotomous variables were in perfect agreement. To test the sensitivity of the smile chart, differences between the two age groups were assessed as differences because aging is expected. In the older age group, philtrum height and visibility of mandibular incisors were significantly larger, whereas the upper lip fullness and buccal corridor visibility were significantly lesser (P <0.001). CONCLUSIONS: The newly developed smile chart can record essential smile parameters to aid diagnosis, treatment planning, and research. The chart is simple and easy to use, has face and content validity and good reliability.

Robustness in phenotypic plasticity and heterogeneity patterns enabled by EMT networks.

Epithelial-mesenchymal plasticity (EMP) is a key arm of cancer metastasis and is observed across many contexts. Cells undergoing EMP can reversibly switch between three classes of phenotypes: epithelial (E), mesenchymal (M), and hybrid E/M. While a large number of multistable regulatory networks have been identified to be driving EMP in various contexts, the exact mechanisms and design principles that enable robustness in driving EMP across contexts are not yet fully understood. Here, we investigated dynamic and structural robustness in EMP networks with regard to phenotypic heterogeneity and plasticity. We use two different approaches to simulate these networks: a computationally inexpensive, parameter-independent continuous state space Boolean model, and an ODE-based parameter-agnostic framework (RACIPE), both of which yielded similar phenotypic distributions. While the latter approach is useful for measurements of plasticity, the former model enabled us to extensively investigate robustness in phenotypic heterogeneity. Using perturbations to network topology and by varying network parameters, we show that multistable EMP networks are structurally and dynamically more robust compared with their randomized counterparts, thereby highlighting their topological hallmarks. These features of robustness are governed by a balance of positive and negative feedback loops embedded in these networks. Using a combination of the number of negative and positive feedback loops weighted by their lengths, we identified a metric that can explain the structural and dynamical robustness of these networks. This metric enabled us to compare networks across multiple sizes, and the network principles thus obtained can be used to identify fragilities in large networks without simulating their dynamics. Our analysis highlights a network topology-based approach to quantify robustness in the phenotypic heterogeneity and plasticity emergent from EMP networks.

Twist1 induces chromosomal instability (CIN) in colorectal cancer cells.

Twist1 is a basic helix-loop-helix transcription factor, essential during early development in mammals. While Twist1 induces epithelial-to-mesenchymal transition (EMT), here we show that Twist1 overexpression enhances nuclear and mitotic aberrations. This is accompanied by an increase in whole chromosomal copy number gains and losses, underscoring the role of Twist1 in inducing chromosomal instability (CIN) in colorectal cancer cells. Array comparative genomic hybridization (array CGH) analysis further shows sub-chromosomal deletions, consistent with an increased frequency of DNA double strand breaks (DSBs). Remarkably, Twist1 overexpression downmodulates key cell cycle checkpoint factors-Bub1, BubR1, Mad1 and Mad2-that regulate CIN. Mathematical simulations using the RACIPE tool show a negative correlation of Twist1 with E-cadherin and BubR1. Data analyses of gene expression profiles of patient samples from The Cancer Genome Atlas (TCGA) reveal a positive correlation between Twist1 and mesenchymal genes across cancers, whereas the correlation of TWIST1 with CIN and DSB genes is cancer subtype-specific. Taken together, these studies highlight the mechanistic involvement of Twist1 in the deregulation of factors that maintain genome stability during EMT in colorectal cancer cells. Twist1 overexpression enhances genome instability in the context of EMT that further contributes to cellular heterogeneity. In addition, these studies imply that Twist1 downmodulates nuclear lamins that further alter spatiotemporal organization of the cancer genome and epigenome. Notwithstanding their genetic background, colorectal cancer cells nevertheless maintain their overall ploidy, while the downstream effects of Twist1 enhance CIN and DNA damage enriching for sub-populations of aggressive cancer cells.

Roadmap on plasticity and epigenetics in cancer.

The role of plasticity and epigenetics in shaping cancer evolution and response to therapy has taken center stage with recent technological advances including single cell sequencing. This roadmap article is focused on state-of-the-art mathematical and experimental approaches to interrogate plasticity in cancer, and addresses the following themes and questions: is there a formal overarching framework that encompasses both non-genetic plasticity and mutation-driven somatic evolution? How do we measure and model the role of the microenvironment in influencing/controlling non-genetic plasticity? How can we experimentally study non-genetic plasticity? Which mathematical techniques are required or best suited? What are the clinical and practical applications and implications of these concepts?

Multistability and predominant hybrid phenotypes in a four node mutually repressive network of Th1/Th2/Th17/Treg differentiation.

Elucidating the emergent dynamics of cellular differentiation networks is crucial to understanding cell-fate decisions. Toggle switch - a network of mutually repressive lineage-specific transcription factors A and B - enables two phenotypes from a common progenitor: (high A, low B) and (low A, high B). However, the dynamics of networks enabling differentiation of more than two phenotypes from a progenitor cell has not been well-studied. Here, we investigate the dynamics of a four-node network A, B, C, and D inhibiting each other, forming a toggle tetrahedron. Our simulations show that this network is multistable and predominantly allows for the co-existence of six hybrid phenotypes where two of the nodes are expressed relatively high as compared to the remaining two, for instance (high A, high B, low C, low D). Finally, we apply our results to understand naïve CD4+ T cell differentiation into Th1, Th2, Th17 and Treg subsets, suggesting Th1/Th2/Th17/Treg decision-making to be a two-step process.

Thrombus Attenuation Gradient Can Predict Successful First-Pass Recanalization Following Stentriever Thrombectomy.

OBJECTIVE: Computed tomography angiography (CTA) derived thrombus enhancement characteristics can predict first-pass recanalization. We studied whether dynamic contrast kinetics within the clot in multiphase CTA can predict first-pass recanalization following stentriever thrombectomy. METHODS: Patients with acute large vessel occlusive stroke evaluated with multiphasic CTA who underwent stentriever thrombectomy were selected. Thrombus perviousness on various phases including arterial, venous, and delayed phases was calculated. Thrombus attenuation gradient (TAG), defined as average attenuation difference between adjacent phases, was also evaluated and correlated with successful first-pass outcome (modified Treatment in Cerebral Ischemia score ≥2b). RESULTS: Of 69 patients, 32 (47%) had successful first-pass recanalization (group 1), and 37 (53%) required >1 attempt (group 2). TAG showed significant differences in arterial-plain and venous-arterial phases. The early increase in TAG was seen in group 1 in the arterial-plain phase, as opposed to group 2 (12.6 vs. 9, P = 0.01), which plateaued in the venous-arterial phase for group 1 and showed a further increase in group 2 (2.1 vs. 5.1, P = 0.02). A cutoff value of 9.2 HU for arterial-plain phase (P = 0.001) and 4.2 HU (P = 0.001) for venous-arterial phase was predictive of first-pass effect. Combining 2 metrics had an odds ratio of 2.8 for first-pass recanalization (P = 0.035). Accuracy evaluated in a validation cohort yielded 74%. Other features including histology were not significant. CONCLUSIONS: TAG evaluated from multiphase CTA can predict first-pass effect in stentriever thrombectomy.

Multi-contrast echo-planar imaging sequence (Echo-planar imaging mix) in clinical situations demanding faster MRI-brain scans.

Objectives: The excellent resolution offered by magnetic resonance imaging (MRI) has a trade-off in the form of scan duration. The purpose of the present study was to assess the clinical utility of echo-planar imaging mix (EPIMix), an echo-planar imaging-based MRI sequence for the brain with a short acquisition time. Materials and Methods: This was a retrospective observational study of 50 patients, who could benefit from faster MRI brain scans. The T1, T2, fluid attenuated inversion recovery, diffusion-weighted imaging (DWI), and T2*/susceptibility-weighted imaging sequences were acquired, conventionally and with EPIMix. Conventional and EPIMix images were assessed by two radiologists for overall quality, motion, and susceptibility artifacts and scored on a Likert scale. The scores given for conventional and EPIMix images were compared. The diagnostic performance of EPIMix was also assessed by the ability to detect clinically relevant findings. Results: The acquisition time for conventional MRI was 11 min and 45 s and for EPIMix 1 min and 15 s. All EPIMix images were sufficient for diagnostic use. On assessment of the diagnostic performance, it was excellent for ischemic and hemorrhagic strokes. Smaller lesions, lesions adjacent to bone, and post-operative tumors were difficult to identify. Moderate to perfect agreement (Kappa values 0.41-1) was seen between radiologists for all categories except skull base, calvarial, and orbital lesions. Image quality, artifact assessment showed excellent interobserver agreement (>90%) for the scores. All EPIMix images showed reduced motion artifacts. The EPIMix-DWI was comparable to conventional-DWI in terms of quality and artifacts. The remaining sequences showed reduced quality and increased susceptibility. Conclusion: The EPIMix has a significantly reduced acquisition time than conventional MRI and could be used instead of conventional MRI in situations demanding faster scans such as suspected acute ischemic or hemorrhagic stroke. In other clinical scenarios, it could help tailor the MRI examination for each patient.

Effectiveness of basic life support training course intervention among dental practitioners and students - An experimental study.

Aim: To determine the level of knowledge and skill of basic life support (BLS) among undergraduate, postgraduate students, and general practitioners with and without regular attendance of the BLS Healthcare Provider course. Methodology: The study was carried out at two intervals with two groups. A random sample involving undergraduate students, postgraduate students, and dental professionals was selected for both study groups. Group 1 with 440 participants had not attended BLS for Healthcare Providers Course in the last two years. Group 2 with 410 participants had attended the BLS for Healthcare Providers course regularly once a year. First, participants in Group 1 were evaluated using an MCQ test with 30 questions about their knowledge and skills in BLS. Then, a well-trained BLS instructor team from Dental College & Hospital offered BLS healthcare provider courses to students and dentists. Subsequently, Group 2 participants who had completed a BLS course for healthcare providers last year were also assessed for their knowledge and skills in BLS using another MCQ test. Results: The marks obtained in the tests were tabulated and analyzed. To determine the association between variables with respect to mean knowledge score, t-test was employed. Multiple group comparison was made using analysis of variance and P < 0.05 was considered statistically significant. The group 1 participants score a mean of 5.7 marks against the Group 2 with a mean score of 27.4 marks out of 30 marks. Knowledge and skill in BLS skills among those in Group 1 without prior BLS training was mainly low. Dental practitioners performed marginally better than students in both groups. Conclusions: Based on the results, we make the following observations. With the introduction of BLS training into the academic curriculum and routine BLS hands-on workshops, all healthcare providers will be familiar with the BLS skills to effectively manage the life-threatening emergencies.

A multi-centric, single-blinded, randomized, parallel-group study to evaluate the effectiveness of nasoalveolar moulding treatment in non-syndromic patients with complete unilateral cleft lip, alveolus and palate (NAMUC study): a study protocol for a randomized controlled trial.

BACKGROUND: Cleft lip and palate (CLP) are among the most common congenital anomaly that affects up to 33,000 newborns in India every year. Nasoalveolar moulding (NAM) is a non-surgical treatment performed between 0 and 6 months of age to reduce the cleft and improve nasal aesthetics prior to lip surgery. The NAM treatment has been a controversial treatment option with 51% of the cleft teams in Europe, 37% of teams in the USA and 25 of cleft teams in India adopting this methodology. This treatment adds to the already existing high burden of care for these patients. Furthermore, the supporting evidence for this technique is limited with no high-quality long-term clinical trials available on the effectiveness of this treatment. METHOD: The NAMUC study is an investigator-initiated, multi-centre, single-blinded randomized controlled trial with a parallel group design. The study will compare the effectiveness of NAM treatment provided prior to lip surgery against the no-treatment control group in 274 patients with non-syndromic unilateral complete cleft lip and palate. The primary endpoint of the trial is the nasolabial aesthetics measured using the Asher McDade index at 5 years of age. The secondary outcomes include dentofacial development, speech, hearing, cost-effectiveness, quality of life, patient perception, feeding and intangible benefits. Randomization will be carried out via central online system and stratified based on cleft width, birth weight and clinical trial site. DISCUSSION: We expect the results from this study on the effectiveness of treatment with NAM appliance in the long term along with the cost-effectiveness evaluation can eliminate the dilemma and differences in clinical care across the globe. TRIAL REGISTRATION: ClinicalTrials.gov CTRI/2022/11/047426 (Clinical Trials Registry India). Registered on 18 November 2022. The first patient was recruited on 11 December 2022. CTR India does not pick up on Google search with just the trial number. The following steps have to be carried out to pick up. How to search: ( https://ctri.nic.in/Clinicaltrials/advsearch.php -use the search boxes by entering the following details: Interventional trial > November 2022 > NAMUC).

Assessing biological network dynamics: comparing numerical simulations with analytical decomposition of parameter space.

Mathematical modeling of the emergent dynamics of gene regulatory networks (GRN) faces a double challenge of (a) dependence of model dynamics on parameters, and (b) lack of reliable experimentally determined parameters. In this paper we compare two complementary approaches for describing GRN dynamics across unknown parameters: (1) parameter sampling and resulting ensemble statistics used by RACIPE (RAndom CIrcuit PErturbation), and (2) use of rigorous analysis of combinatorial approximation of the ODE models by DSGRN (Dynamic Signatures Generated by Regulatory Networks). We find a very good agreement between RACIPE simulation and DSGRN predictions for four different 2- and 3-node networks typically observed in cellular decision making. This observation is remarkable since the DSGRN approach assumes that the Hill coefficients of the models are very high while RACIPE assumes the values in the range 1-6. Thus DSGRN parameter domains, explicitly defined by inequalities between systems parameters, are highly predictive of ODE model dynamics within a biologically reasonable range of parameters.

Landscape of epithelial-mesenchymal plasticity as an emergent property of coordinated teams in regulatory networks.

Elucidating the design principles of regulatory networks driving cellular decision-making has fundamental implications in mapping and eventually controlling cell-fate decisions. Despite being complex, these regulatory networks often only give rise to a few phenotypes. Previously, we identified two 'teams' of nodes in a small cell lung cancer regulatory network that constrained the phenotypic repertoire and aligned strongly with the dominant phenotypes obtained from network simulations (Chauhan et al., 2021). However, it remained elusive whether these 'teams' exist in other networks, and how do they shape the phenotypic landscape. Here, we demonstrate that five different networks of varying sizes governing epithelial-mesenchymal plasticity comprised of two 'teams' of players - one comprised of canonical drivers of epithelial phenotype and the other containing the mesenchymal inducers. These 'teams' are specific to the topology of these regulatory networks and orchestrate a bimodal phenotypic landscape with the epithelial and mesenchymal phenotypes being more frequent and dynamically robust to perturbations, relative to the intermediary/hybrid epithelial/mesenchymal ones. Our analysis reveals that network topology alone can contain information about corresponding phenotypic distributions, thus obviating the need to simulate them. We propose 'teams' of nodes as a network design principle that can drive cell-fate canalization in diverse decision-making processes.

Single-cell analysis reveals X upregulation is not global in pre-gastrulation embryos.

In mammals, transcriptional inactivation of one X chromosome in female compensates for the dosage of X-linked gene expression between the sexes. Additionally, it is believed that the upregulation of active X chromosome in male and female balances the dosage of X-linked gene expression relative to autosomal genes, as proposed by Ohno. However, the existence of X chromosome upregulation (XCU) remains controversial. Here, we have profiled gene-wise dynamics of XCU in pre-gastrulation mouse embryos at single-cell level and found that XCU is dynamically linked with X chromosome inactivation (XCI); however, XCU is not global like XCI. Moreover, we show that upregulated genes are enriched with activating marks and have enhanced burst frequency. Finally, our In-silico model predicts that recruitment probabilities of activating factors and a surge of these factors upon X-inactivation trigger XCU. Altogether, our study provides significant insight into the gene-wise dynamics and mechanistic basis of XCU during early development and extends support for Ohno's hypothesis.

Emergent properties of coupled bistable switches.

Understanding the dynamical hallmarks of network motifs is one of the fundamental aspects of systems biology. Positive feedback loops constituting one or two nodes - self-activation, toggle switch, and double activation loops - are the commonly observed motifs in regulatory networks underlying cell-fate decision systems. Their individual dynamics are well studied; they are capable of exhibiting bistability. However, studies across various biological systems suggest that such positive feedback loops are interconnected with one another, and design principles of coupled bistable motifs remain unclear. What happens to the bistability or multistability traits and the phenotypic space (collection of phenotypes exhibited by a system) due to the couplings? In this study, we explore a set of such interactions using discrete and continuous simulation methods. Our results suggest that the most frequent states in coupled networks follow the 'rules' within a motif (double activation, toggle switch) and those across the two motifs in terms of how the two motifs have been coupled. Moreover, 'hybrid' states can be observed, too, where one of the above-mentioned 'rules' can be compromised, leading to a more diverse phenotypic repertoire. Furthermore, adding direct and indirect selfactivations to these coupled networks can increase the frequency of multistability. Thus, our observations revealed specific dynamical traits exhibited by various coupled bistable motifs.

Functional Resilience of Mutually Repressing Motifs Embedded in Larger Networks.

Elucidating the design principles of regulatory networks driving cellular decision-making has important implications for understanding cell differentiation and guiding the design of synthetic circuits. Mutually repressing feedback loops between 'master regulators' of cell fates can exhibit multistable dynamics enabling "single-positive" phenotypes: (high A, low B) and (low A, high B) for a toggle switch, and (high A, low B, low C), (low A, high B, low C) and (low A, low B, high C) for a toggle triad. However, the dynamics of these two motifs have been interrogated in isolation in silico, but in vitro and in vivo, they often operate while embedded in larger regulatory networks. Here, we embed these motifs in complex larger networks of varying sizes and connectivity to identify hallmarks under which these motifs maintain their canonical dynamical behavior. We show that an increased number of incoming edges onto a motif leads to a decay in their canonical stand-alone behaviors. We also show that this decay can be exacerbated by adding self-inhibition but not self-activation loops on the 'master regulators'. These observations offer insights into the design principles of biological networks containing these motifs and can help devise optimal strategies for the integration of these motifs into larger synthetic networks.

Emergence of hybrid states of stem-like cancer cells correlates with poor prognosis in oral cancer.

Cancer cell state transitions emerged as powerful mechanisms responsible for drug tolerance and overall poor prognosis; however, evidences were largely missing in oral cancer. Here, by multiplexing phenotypic markers of stem-like cancer cells (SLCCs); CD44, CD24 and aldehyde dehydrogenase (ALDH), we characterized diversity among multiple oral tumor tissues and cell lines. Two distinct patterns of spontaneous transitions with stochastic bidirectional interconversions on 'ALDH-axis', and unidirectional non-interconvertible transitions on 'CD24-axis' were observed. Interestingly, plastic 'ALDH-axis' was harnessed by cells to adapt to a Cisplatin tolerant state. Furthermore, phenotype-specific RNA sequencing suggested the possible maintenance of intermediate hybrid cell states maintaining stemness within the differentiating subpopulations. Importantly, survival analysis with subpopulation-specific gene sets strongly suggested that cell-state transitions may drive non-genetic heterogeneity, resulting in poor prognosis. Therefore, we have described the phenotypic-composition of heterogeneous subpopulations critical for global tumor behavior in oral cancer; which may provide prerequisite knowledge for treatment strategies.

A reciprocal feedback loop between HIF-1α and HPIP controls phenotypic plasticity in breast cancer cells.

While phenotypic plasticity is a critical factor contributing to tumor heterogeneity, molecular mechanisms underlying this process are largely unknown. Here we report that breast cancer cells display phenotypic diversity in response to hypoxia or normoxia microenvironments by operating a reciprocal positive feedback regulation of HPIP and HIF-1α. We show that under hypoxia, HIF-1α induces HPIP expression that establishes cell survival, and also promotes cell migration/invasion, EMT and metastatic phenotypes in breast cancer cells. Mechanistic studies revealed that HPIP interacts with SRP14, a component of signal recognition particle, and stimulates MMP9 synthesis under hypoxic stress. Whereas, in normoxia, HPIP stabilizes HIF-1α, causing the Warburg effect to support cell growth. Concurrently, mathematical modelling corroborates this reciprocal feedback loop in enabling cell-state transitions in cancer cells. Clinical data indicate that elevated levels of HPIP and HIF-1α correlate with unfavorable prognosis and shorter survival rates in breast cancer subjects. Together, this data shows a reciprocal positive feedback loop between HPIP and HIF-1α that was unknown hitherto. It unveils how the tumor microenvironment influences phenotypic plasticity that has an impact on tumor growth and metastasis and, further signifies considering this pathway as a potential therapeutic target in breast cancer.