ECM (collagen) mediated signaling drives the emergence of androgen independence in prostate cancer cells.

1
Introduction
Tumor microenvironment (TME) is a heterogenous mixture of both cellular (tumor cells, fibroblasts, endothelial cells, adipocytes, immune cells and neuroendocrine cells) and acellular components (extracellular matrix proteins, antibodies, cytokines, extracellular vesicles, growth factors and metabolites). The tumor behavior is not solely defined by the factors produced by the tumor itself, but also heavily influenced by the complex interaction between the tumor and its microenvironment. This interaction is what shapes the tumor microenvironment and influences cancer cell survival, immune surveillance, angiogenesis, local invasion, metastasis and therapeutic response [1]. Previously, tumor intrinsic factors were considered the primary reason for therapy resistance and cancer progression. However, recent research studies have demonstrated that components of the extracellular matrix (ECM) and other factors within TME contribute significantly to tumor behavior and therapeutic failure (reviewed in Refs. [[2], [3], [4]]).
ECM is a 3D network of macromolecules that provides structural and biochemical support to cells [5]. Animal ECM can be classified into two main components: the interstitial matrix, which surrounds the cells, providing structural support and facilitating cell-cell communication; and the basement membrane, a thin sheet that separates the stroma from cells of various origins, playing a key role in tissue integrity and function [6]. In cancer, ECM is biochemically different and significantly stiffer than normal ECM. It undergoes extensive remodeling and contributes significantly to cancer cell proliferation, survival, metastasis and response to therapy [5].
Collagen is one of the most abundant components of the ECM and contributes about 30% of the total body protein [7,8]. Collagen is a structural protein that provides structural support to the extracellular space of connective tissue. Due to its rigidity and structural resistance, it serves as an ideal scaffold for skin, tendons, bones and ligaments. Collagens are classified into various types based on the type of structures they form. The most common types are type I and type IV. Type I comprises over 90% of the collagen in the human body [9]. Collagens are typically homo or heterotrimers composed of one, two, or three different polypeptide chains [7]. Collagen is critical in shaping tumor behavior; tumor cells reverse the process by reshaping collagen to form a reinforcing cell-collagen loop. This dynamic and reciprocal interaction would gradually foster cancer progression [10]. Adhesion of COLI and COLIV to cancer cells impacts cancer progression [11].
Collagen fibres constitute the major structural component of the ECM in the normal prostate stroma. Among these, collagen type I and type III are the predominant fibrillar collagens, whereas collagen type IV is primarily localised in the basement membrane (reviewed in Refs. [12,13]). Excessive synthesis of type 1 collagen has been observed to activate periacinar fibroblasts adjacent to prostatic intraepithelial neoplasia, a precursor lesion of prostatic adenocarcinoma. This suggests that increased collagen production within the prostate is associated with the development and progression of prostate cancer (PCa) [14,15]. An integrative study by Xiao, Y., Lai, C., Hu, J. et al. reported that collagen-associated genes like PLOD3, COLA1, MMP11 and FMOD could potentially act as a prognostic marker for biochemical recurrence-free survival of patients [16]. Differential expression of collagen has been observed between benign prostate hyperplasia (BPH) and prostate cancer. For example, PLOD3, a collagen-associated gene, is differentially expressed in cancer and para-cancer prostate tissues of clinical specimens [16]. Collagen XXII protein levels are significantly elevated in prostate cancer compared to benign prostate tissue. Notably, collagen XXII expression is higher in distant metastases or prostate cancer compared to either localized or regional (lymph node) metastases [17]. Furthermore, patients exhibiting higher levels of collagen XXII expression demonstrate a 2.8-fold increased risk of PSA recurrence. This suggests that distinct patterns of collagen expression may serve as a potential biomarkers for monitoring prostate cancer progression and metastasis [17,18].
Over the last decade several studies have demonstrated that ECM/integrin signaling provide survival advantage to cancer cells against various therapies reviewed in Ref. [19]. The binding of collagen to integrin and subsequent downstream events supports tumor growth and progression. This interaction could also result in the activation of certain downstream signaling pathways such as FAK, PI3K/AKT and ERK. Activation of these pathways enhance cell survival, proliferation, migration and therapy resistance, collectively contributing to disease progression and reduced treatment efficacy [20].
Our group has previously profiled gene expression from prostate cancer and compared it with non-cancerous prostate (BPH) [21]. We have also performed a comparative transcriptomic analysis of fibroblasts from control and cancerous prostate (CAFs) [1], as well as a quantitative mass spectrometry analysis on the conditioned media of cultured fibroblasts (control vs CAFs). From all these data sets, collagen/s emerged as a common overexpressed gene [22].
The current study is focused on understanding a. Whether collagen/s influences prostate cancer cell proliferation and aggressiveness and b. Whether collagen/s can promote development of androgen independence by initiating signaling cross-talk.

2
Materials and methods
2.1
Cell culture
Prostate cancer cell lines LNCaP, DU145 and PC3 were procured from the National Centre for Cell Science (NCCS), Pune, India. LNCaP cells were grown and maintained in Rosewell Park Memorial Institute-1640 (RPMI-1640) (Thermo Fischer Scientific, Cat no: 23400-021) media containing 15% fetal bovine serum (heat inactivated) (Thermo Fischer Scientific, Cat no: 10270), 1X PenStrep (Thermo Fischer Scientific, Cat no: 15140122) and 1X Glutamax (Thermo Fischer Scientific, Cat no: 35050061), whereas PC3 and DU145 cells were maintained in DMEM-F12 (Thermo Fischer Scientific, Cat no: 12400024) media supplemented with 10% FBS, 1X PenStrep and 1X Glutamax. All cells were maintained in a humidified 37 °C incubator maintaining 5% CO2.

2.2
Collagen coating and treatment with growth factors and inhibitors
Lyophilized collagen (Merck Roche, Cat no: 11179179001) was reconstituted using Dulbecco's phosphate-buffered saline (DPBS) (Thermo Fischer Scientific, Cat no: 21600-010) containing 0.1% acetic acid. The reconstituted collagen was then coated on the plates or wells at a concentration of 5 μg/cm2 according to manufacturer's instruction.
Following collagen coating, cells were seeded in plates/wells containing growth media. After 6- 8 h of seeding, the cells were treated with the required amount of inhibitors or growth factors for 48hrs in serum-free media. The drug was replenished after 48hrs. The control/vehicle cells were treated with DMSO. At 72hrs, the RNA was isolated and converted to cDNA. The concentration of activators and inhibitors used is summarized in Table 1. The list shows the drug name, manufacturing company, catalog number, abbreviations and concentration used in the current study.

2.3
RNA isolation
Total RNA was isolated using RDP trio reagent (Himedia, Cat No: 15596026) according to the manufacturer's instructions. RNA was quantified on a nanodrop (Thermo Scientific™ NanoDrop™). The quality of RNA samples was assessed by running them on a 1% agarose gel.

2.4
qRT-PCR
2 μg RNA was converted to cDNA using Verso cDNA synthesis kit (Thermo Fisher Scientific Cat no: AB1453A) according to manufacturer's instructions. 20 ng RNA equivalent cDNA was used for the PCR reactions. qRT-PCR was carried out using the Kapa SYBR FAST Universal 2XqPCR Master Mix (Roche, Cat no: KK4601). RPL35 served as an internal control. The expression levels of each gene test sample relative to the control were analyzed using the ddCt method [23]. Relative fold changes with respect to control/vehicle samples were plotted in the graphs. Experiments were repeated 3 times and each PCR done in triplicates. The graphs presented in results section are consolidated results of 3 experiments. For all the qRT-PCR experiments, the raw CT values are presented in supplementary tables. Details of the primers used in the current are listed in Supplementary Table 1.

2.5
Chemosensitivity assay
0.05X106 cells/well were plated in a 24-well plate (either collagen-coated or plain surface) and allowed to attach. After 6-8 h of incubation, docetaxel, a commonly used chemotherapeutic drug was added to each in increasing concentration (6 different concentrations of drug, including vehicle). The drug was replenished after 48hrs. The control/vehicle cells were treated with DMSO. After 72hrs, the cells were trypsinized and counted using the trypan blue exclusion assay. Cell suspension was mixed with equal volume of trypan blue dye and counted using Countess (Countess® II FL). The percentage of viable cells was calculated using the formula.
Percentage viability = (No. of viable cells/Total no. of cells) X 100.
For each condition, the cells were plated in duplicate wells and each well was counted twice. The entire experiment was repeated 3 times and the average has been plotted.

2.6
Migration assay
A total of 4 × 106 cells were plated onto a 60 mm dish (either collagen-coated or plain surface) and allowed to grow until they formed a confluent monolayer. A scratch/wound was made in each dish using a 200 μL micropipette tip. The width of the scratch was measured every hour using the Nikon NIS Element software in conjunction with a light microscope at 10X magnification. At each time point, three readings were taken and the average distance was calculated. The rate of migration was calculated using the formula

2.7
Cell viability assay (MTT)
5000 cells/well were plated in the 96-well plate (either collagen-coated or plain surface) and allowed to attach. After 6-8 h of incubation, inhibitors/activators were added to serum-free media. The drug was replenished after 48hrs. At 72 h, MTT reagent was added to the wells (0.5 mg/mL). After the formation of violet formazan crystals, the crystals were dissolved using laboratory-grade 100% DMSO. OD was measured at 570 nm. The experiment was repeated 3 times and the average has been plotted.

2.8
Statistical analyses
Statistical analyses were performed using GraphPad Prism V8 (GraphPad Software, USA). Data is presented as mean ± SEM from three independent experiments. Comparisons between two groups were performed using unpaired two-tailed Student t-test. For multiple group comparison, two-way ANOVA with Tukey's post hoc test was used. Dose-response curves were generated using non-linear regression (curve fit). IC50 values were calculated from fitted curves with 95% confidence intervals. A p-value <0.05 was considered statistically significant.

3
Results
3.1
Expression levels of various collagen types across transcriptomic and proteomic datasets
Previously, our group has conducted three studies namely differential gene expression on castrate sensitive and castrate resistant prostate cancer in comparison to BPH; comparative transcriptome analysis between fibroblasts derived from BPH and prostate cancer; comparative secretome analysis between fibroblasts derived from BPH and prostate cancer [1,21,22]. Different collagens were found to be overexpressed in prostate cancer/CAFs, This data is summarized in Table 2.
Since many collagens have been seen to be overexpressed, for our functional studies, we have used a commercially available collagen which is a mixture of collagens.

3.2
Validation of collagen overexpression in CAFs
Various transcriptomic and proteomic datasets generated in our laboratory revealed the overexpression of different subsets of the collagen family. To validate some of these omics-based observations, we have performed qRT-PCR to assess the expression of COL11A1 gene in RNA isolated from control fibroblasts and cancer-associated fibroblasts. This gene was overexpressed in two of our datasets and hence chosen for validation. Analysis demonstrated the significant overexpression of the COL11A1 gene in CAFs compared to control fibroblasts (Fig. 1).

3.3
Effect of collagen on the sensitivity of prostate cancer cell lines to docetaxel
We evaluated the sensitivity of prostate cancer cell lines (LNCaP, DU145 and PC3) to the common chemotherapeutic drug docetaxel (commonly used to treat and manage metastatic castrate resistance prostate cancer) in the presence of collagen. The cell viability was estimated using trypan blue exclusion assay and the percentage viability was calculated at different concentrations of the drug. Two-way ANOVA followed by post hoc analysis revealed a significant effect of drug dose and collagen coating (p < 0.0001) on cell viability. Dose-response curves were generated using non-linear regression (curve fit). IC50 values were calculated from fitted curves with 95% confidence intervals.
The results exhibited a shift in the IC50 towards a higher concentration in the presence of collagen when compared to control conditions [LNCaP 2.14 nM (95% CI: 1.89-2.4) vs 1.3 nM (95% CI: 1.04-1.63); DU145 2.7 nM (95% CI: 2.32-3.2) vs 1.98 nM (95% CI: 1.05-2.6) and PC3 2.34 nM (95% CI: 1.85-2.87) vs 1.38 nM (95% CI: 0.67-2.21)]. This suggests that the presence of collagen makes LNCaP cells more tolerant to chemotherapeutic drugs (Fig. 2). However, DU145 and PC3 show marginal changes in drug tolerance in the presence of collagen. Table 3 shows the IC50 of docetaxel across different prostate cancer cell lines cultured either on a plain or a collagen-coated surface.

3.4
Effect of collagen on the migratory ability of cells
LNCaP, DU145 and PC3 cells were grown to confluence on either collagen-coated or plain 60 mm dishes. A wound was created in the cell monolayer and the width of the wound was measured every hour. The rate of migration was calculated. No change in rate of migration was observed in the LNCaP cells cultured on the collagen-coated surfaces when compared to cells cultured on plain surfaces (1.18μ/hr vs 1.27μ/hr). A marginal increase in rate of migration was observed in cells grown on collagen-coated dishes compared to those on plain dishes in DU145 (7.1 ± 1.4μ/hr vs 6.5 ± 1.6μ/hr) and PC3 (4.2 ± 0.94μ/hr vs 3.4 ± 0.52μ/hr) (Fig. 3). The wound closure was assessed within a time period which is less than the doubling time of these cells (the doubling time of PC3 is between 30 and 48hr, DU145 is between 30 and 40hr and LNCaP is between 48 and 72hr [24]. Therefore, the observed wound closure is unlikely by cell proliferation. Table 4 represents the average rate of migration of three experiments (Fig. 4).
Note: Due to technical constraints, the wound healing assay in LNCaP cells was conducted in a single experiment. The rate of migration reported in the current study for LNCaP cells is derived from this single experiment and hence no statistics shown.

3.5
Effect of collagen on stem-cell marker expression
LNCaP, DU145 and PC3 cells were grown to confluence on either collagen-coated or plain 60 mm dishes. RNA was isolated and converted to cDNA. 20 ng of RNA equivalent cDNA was used to perform stem cell marker analysis by qRT-PCR (c-MYC, KLF4, SOX2 and OCT4). The expression was normalized to the RPL35. c-MYC showed reduced expression in LNCaP cells, whereas in DU145 and PC3 cells, there was an increased expression in response to collagen. KLF4 shows no significant change; SOX2 shows reduced expression in DU145 and PC3 cells; OCT4 shows increased expression in LNCaP and PC3 cells (Fig. 5A, B and 5C). Based on these results, the effect of collagen on stem-cell marker expression appears to be cell-specific. Results are summarized in Table 5. Student t-test was performed to analyse the significance. The raw CT values are presented in Supplementary Table 2.
In order to assess whether presence of collagen influences the stemness of the cancer cells, a clonogenicity assay was performed. However, this assay did not yield any conclusive results (Supplementary Fig. 1).

3.6
Effect of collagen on AR signaling
LNCaP cells are AR positive and sensitive to androgens as well as anti-androgens such as flutamide. DU145 cells contain a mutant AR gene and PC3 lacks AR expression. These cells, therefore, do not respond to androgen treatments and hence these have not been used for any AR-related experiments.
Prostate-specific antigen (PSA) expression serves as a well-established direct measure of active AR signaling [25]. Hence this has been used as a read-out of AR signaling in all the experiments.

3.7
Effect of FAK on androgen signaling
To assess the effect of collagen on AR-target genes, LNCaP cells were cultured on either collagen-coated or plain dishes and qRT-PCR for PSA gene was performed. A 1.25-fold increased expression of the PSA was observed in the presence of collagen (Fig. 6).
In order to ascertain whether this increase in PSA expression was due to signaling initiated by collagen via Focal Adhesion Kinase (FAK), a FAK inhibitor (FAKi), PF 573228, was used. 5μΜ flutamide was used to create androgen-deprived conditions [26,27]. RNA was isolated and PSA expression was estimated.
Flutamide decreased the expression of PSA by 1.78-fold and 1.49-fold in plain and collagen coated cells respectively (Fig. 7A). FAK inhibitor also significantly reduced PSA expression (Fig. 7B) in both plain (3.4-fold) and collagen-coated surfaces (2.17-fold). Furthermore, the combination of PF 573228 with flutamide also resulted in a significant decrease in PSA expression by 2.8-fold and 1.8 fold in both plain and collagen-coated cells respectively (Fig. 7C). The raw CT values are presented in Supplementary Table 3.

3.8
Effect of collagen on the EGFR pathway under androgen-deprived conditions
The role of the EGFR pathway in various cancers is well established. However, the role of this pathway in the development of androgen independence remains inadequately understood.
Also, there are emerging evidences highlighting the cross-talk between FAK and EGFR pathway activation [28]. In order to elucidate the role of EGFR pathway under androgen-deprived conditions, erlotinib, an EGFR pathway inhibitor was utilized. Cells were plated either on plain or collagen-coated surface and RNA was collected after 48hrs of treatment. The expression of PSA was estimated using qRT-PCR. EGF treatment increased the expression of PSA in both collagen-coated (1.04-fold) and plain surface (1.75 -fold). Erlotinib treatment led to a reduction in PSA expression (by 3.7-fold in plain and 2.27-fold in collagen-coated), which was partially restored by EGF co-treatment in both collagen-coated (1.75-fold) and plain surface (1.35-fold) (Fig. 8A).
In the presence of erlotinib, EGF was unable to rescue the PSA expression under androgen-deprived (flutamide treated) conditions. This was observed both in the collagen-coated (1.8-fold) and plain surface (2.3-fold) (Fig. 8B). The raw CT values are presented in Supplementary Table 4.

3.9
Effect of collagen on cell proliferation
To evaluate the effect of collagen on cell proliferation, MTT assay was performed. The cells were plated either on collagen-coated or plain surfaces and treated with different combinations of inhibitors or activators. The cell viability was estimated using the MTT assay. Two-way ANOVA followed by Tukey's post hoc analysis revealed significant effects of coating (p < 0.0001) and treatment (p < 0.0001), demonstrating that treatment responses differed between plain and collagen-coated conditions. Treatment with dihydrotestosterone (DHT) increased the cell viability in both collagen-coated and plain surface by 44% and 17% respectively (Fig. 9A). Treatment with flutamide resulted in a reduction in cell viability (collagen-coated:27%; plain surface:10%). However, co-treatment with DHT partially restored cell viability in the presence of flutamide. A similar trend was observed with the FAK inhibitor (collagen-coated: 39%; plain surface: 47%); the combination of FAK inhibitor and DHT partially restored the cell viability as observed with flutamide and DHT (Fig. 9B). Notably, while the combination of the FAK inhibitor and flutamide led to a further decrease in cell viability (collagen-coated: 40%; plain surface: 50%), the addition of DHT to this combination did not result in a significant rescue of cell viability (Fig. 9C).
Increased cell proliferation was observed on treatment with EGF in cells cultured on a collagen-coated surface (collagen-coated:28%; plain surface: 8%). On treatment with erlotinib, cell viability was decreased (collagen-coated: 19%; plain surface: 14%) and was partially restored on treatment with EGF (Fig. 9D). A similar trend was observed in the cells treated with a combination of erlotinib, flutamide, and EGF (Fig. 9E).
However, in all these combination treatments, a slightly higher cell viability was observed in the cells grown on a collagen-coated surface compared to those on a plain surface, suggesting that collagen does contribute to enhanced cell proliferation.

4
Discussion
The extracellular matrix is a highly dynamic structure that undergoes continuous deposition, remodeling and degradation to maintain tissue homeostasis [5]. During cancer initiation and progression, ECM undergoes extensive alterations, directly influencing tumor cell proliferation, survival, invasion, migration and metastasis. Increasing evidence indicates that ECM remodeling is a critical driver of tumor growth, invasion and metastasis in prostate cancer. Malignant prostate tissues are almost 60% stiffer than benign prostate tissues [29]. ECM components and their re-organization are emerging as prognostic biomarkers for prostate cancer progression and metastasis. Increased collagen density and reorganization of collagen fibres correlate with the higher Gleason score, as more aligned collagen structures are observed in malignant biopsies compared to non-malignant tissue biopsies. These evidences indicate that increased and remodeled ECM correlates with more aggressive forms of prostate cancer [[29], [30], [31]].
Several studies have investigated the impact of this ECM on cellular pathways. In castrate resistant prostate cancer (CRPC), ECM reorganization has been shown to activate key pathways such as EGFR, PI3K/AKT, and MAPK([[32], [33], [34]]). Notably, matrix remodeling induces the activation of multiple signaling pathways that overlap with those involved in both androgen-dependent and androgen-independent prostate cancer progression. These findings suggest that ECM and ECM related signaling contributes to the molecular mechanisms underlying prostate cancer aggressiveness and therapy resistance.
Collagen is one of the major components of the ECM. Various types of collagens are differentially expressed in cancerous vs non-cancerous tissues, for example, collagen XXII and it can be detected in urine [17,35]. A significant alteration in collagen metabolism has been observed in cancerous tissue compared to adjacent histologically benign prostatic tissue [18]. A study demonstrated that type 1 collagen serves as a primary substrate for PC3 cells, a prostate cancer cell line. Moreover, collagen type 1 was found to significantly enhance PC3 cell proliferation through activation of the PI3K pathway, suggesting that collagen may promote prostate cancer cell metastasis by increasing both cellular attachment and proliferation [36]. Additionally, type 1 collagen was shown to enhance the invasion capacity of the human prostate cancer cell line LNCaP, via α2β1 integrin and RhoC signaling. Treatment of LNCaP cells with a neutralizing antibody against α2β1 integrin decreased collagen-induced in-vitro invasion, indicating that α2β1-mediated signaling facilitates collagen-driven invasion through the upregulation of RhoC. Collectively, these studies suggest that collagen plays a fundamental role in promoting prostate cancer metastasis [37].
However, limited studies have investigated the precise mechanisms by which collagen contributes to cancer progression, highlighting the importance of elucidating the role of collagen in cancer [38,39]. Our study has demonstrated that collagen may activate/influence other signaling pathways and hence contribute to therapeutic resistance (resistance to androgen deprivation).
ECM proteins are known to bind integrins, leading to the activation of the cytoplasmic domain of integrin. This, in turn, triggers the autophosphorylation and activation of FAK. Activated FAK subsequently phosphorylates downstream proteins and initiates and cross-talks with multiple signaling cascades, including androgen receptor signaling by acting as a kinase or as a scaffold protein (reviewed in Ref. [40]).
Additionally, ECM may also influence the EGFR signaling pathway. Integrins present in the ECM, particularly β1 and α5β3 and can physically interact with EGFR, leading to ligand-independent activation of EGFR [41]. The activated EGFR pathway cascade (MAPK, PI3K/AKT) may, in turn, induce the PSA gene transcription through its interaction with the PSA upstream enhancer containing AP-1 binding sites (−4420) [42] (Fig. 10).
Previous results from our group has identified several isoforms of collagen to be overexpressed in prostate cancer. In this study, we attempted to elucidate how this may influence tumor cell behaviour as well as its effect on emergence of androgen independence. While some properties of prostate cancer cells such as migration and chemosensitivity was influenced by the presence of collagen, this was mostly a cell-type specific effect.
The effect of collagen on AR-mediated target gene expression as well as cell proliferation appears to be more significant. These experiments were done on LNCaP cells, which are responsive to androgens as well as androgen inhibition. When cells are grown in the presence of collagen, there is an increased expression of PSA, an androgen receptor-target gene. This increased expression is seen even under conditions of androgen deprivation (achieved by flutamide treatment), but sensitive to inhibition of FAK. Similar results are also seen with cell proliferation. This suggests that collagen-mediated signaling could be an adaptive mechanism of the cells under androgen-deprived conditions.
We have also investigated the effect of EGFR pathway on AR-mediated gene expression and cell proliferation. These results also suggest that EGFR pathway can activate AR-target gene expression even under androgen-deprived conditions making activation of EGFR an adaptive mechanism under conditions of androgen deprivation.
Although it is unclear how FAK and EGFR may be interacting with each other or how they interact with AR (non-canonical AR signaling) and requires further in-depth mechanistic studies, our data suggests that targeting these pathways in combination with AR pathway may be a better therapeutic strategy to manage prostate cancer, particularly in emergence of the androgen-independent phase.
These studies are carried out in 2D cell culture model which do not completely mimic physiological conditions. These do not account for the dynamics of matrix remodeling (deposition and degradation) that occurs in the tumor microenvironment, which in turn influences the matrix stiffness and downstream effects. Regardless of these limitations, our data clearly demonstrates the possibility of ECM-initiated signaling which can substitute for AR-signaling effects such as gene expression and cell proliferation. This particularly becomes important during androgen deprivation therapy (ADT) since this kind of mechanism would promote the emergence of androgen-independence. Therefore, the insights of this study would serve as a reference for developing more effective therapeutic regimen for managing androgen-independent prostate cancer.

Funding
This study was supported by the Indian Council of Medical Research, Govt of India (2019−0937). AA is supported by the Lady Tata Memorial Trust Fellowship. The authors thank the Centre for Human Genetics, Bengaluru and KITS, Government of Karnataka for the support during this study.

CRediT authorship contribution statement
Apoorva Abikar: Formal analysis, Methodology, Validation, Writing – original draft. Prathibha Ranganathan: Conceptualization, Funding acquisition, Project administration, Resources, Supervision, Writing – review & editing.

Declaration of competing interest
The authors declare no conflicts of interest.