Hh and EGFR-Ras signaling promote distinct steps of tumor progression in the Drosophila follicle epithelium

Domain: biology
Published: 2026-03-24
Editorial outcome: major_revision

Abstract
Controlled signaling activity is vital for normal tissue homeostasis and oncogenic signaling activation facilitates tumorigenesis. Here, we combine single-cell transcriptomics with in-depth genetic and imaging analysis to investigate the role of the EGFR-Ras and Hedgehog signaling pathways in homeostasis of the Drosophila follicle stem cell lineage. We find that Hedgehog signaling simultaneously promotes an undifferentiated state and induces differentiation via activation of the epithelial-mesenchymal-transition associated transcription factor Zfh1. Overactivation of Hedgehog signaling generates a mixed transcriptional state comparable to partial epithelial-mesenchymal-transition. EGFR-Ras overactivation induces cell cycle defects by activating the transcription factors Pointed and E2f1 and impedes differentiation. Overactivation of both pathways blocks differentiation and induces tumor-like growth where follicle cells exhibit a loss of tissue architecture, sustained proliferation and a reduced lifespan of the host. These findings provide new insight into how signaling pathways converge at the transcriptional level to prevent malignant cell behavior.

Introduction
Tissue homeostasis is regulated by the activity of signaling pathways that determine cell behaviors such as the rate of proliferation and the spatial and temporal pattern of differentiation. In epithelial tissues with constitutively active stem cells, these processes occur simultaneously within a relatively small region, thus requiring precise control of each signal. Typically, multiple signaling pathways with unique but overlapping roles function in concert to regulate each cellular behavior. The resulting redundancy and regulatory feedback within this signaling network are thought to confer precision and robustness1. Untangling the contribution of different pathways within the same cells has been a challenge, in part because standard approaches such as immunofluorescence to assay for marker expression or pathway reporters examine only a small fraction of the overall transcriptional changes caused by an experimental manipulation. Further, the cellular heterogeneity of most tissues adds additional complexity to the analysis. Signaling pathways that regulate proliferation have also been a major focus of research as they are tightly linked to cancer development2. This includes mutations affecting the activity of the Hedgehog (Hh) and EGFR signaling as well as Ras signaling, which is activated by the EGFR pathway3–5. Indeed, during cancer development, the Hh and EGFR-Ras pathways can interact and synergistically induce gene expression6–8.

The Drosophila follicle stem cell (FSC) lineage is a well-established model for the study of homeostasis in a stem cell based epithelial tissue9. The Drosophila ovary is composed of long strands of developing follicles, called ovarioles, and the follicle epithelium is a layer of somatic cells that surrounds each follicle. The follicle epithelium is maintained by a population of FSCs that reside at the anterior edge of the tissue in a structure called the germarium. The precise number and location of the FSCs has been debated recently10,11, but it is generally agreed that they are located between Regions 2a and 2b of the germarium at or near the anterior boundary of the expression domain of the cell surface marker, Fasciclin 3 (Fas3). FSCs produce transiently amplifying daughter cells, called prefollicle cells (pFCs), which are the precursors for all differentiated follicle cell populations (Fig. 1A). They differentiate into either main body (MB) follicle cells, which ensheath the growing germline cysts, stalk cells, which connect adjacent cysts, or polar cells, which help pattern the follicle and induce stalk cell differentiation. Previous studies using genetics, lineage tracing, and single-cell transcriptomics have revealed that differentiation toward the polar, stalk, or MB follicle cell fate is initiated early in the FSC lineage, at a stage that is well before any morphological distinctions in the pFC population are apparent12–15. At this stage, multiple signaling pathways function together to ensure that each pFC differentiates into the correct cell type at the right time and place. The EGFR-Ras and Hedgehog (Hh) signaling pathways are both required for FSC self-renewal and are important regulators of follicle cell proliferation and differentiation9,16–18. EGFR signaling, which is indirectly activated by Wnt signaling in FSCs, functions upstream of both the Ras/MAPK and the Lkb1/AMPK pathways to promote FSC self-renewal, regulate FSC and pFC proliferation, and establish apical polarity in the early follicle cell lineage16. Hh signaling controls proliferation of FSCs and early pFCs via activation of the Hippo signaling pathway and regulates their differentiation in part through direct and indirect inhibition of the transcription factors, Castor (Cas) and Eyes absent (Eya) (Fig. 1A)14,19–22. Here, we demonstrate that EGFR-Ras signaling and Hh signaling pathway do not cross-regulate each other during homeostasis of the follicle epithelium. We investigate the effects of ectopic pathway activation via single-cell RNA-sequencing, bioinformatic analyses, and in vivo assays and find that ectopic pathway activation predominantly perturbs differentiated cell populations. EGFR-Ras signaling overactivation delays the mitosis-to-endocycle switch in MB follicle cells. Conversely, overactivation of the Hh pathway, acting via the transcription factor and ZEB1/2 ortholog Zfh1, promotes a mixed transcriptional state. This mixed transcriptional state is characterized by a retention of an undifferentiated character and simultaneous differentiation towards the stalk cell fate, accompanied by a partial epithelial-to-mesenchymal transition (EMT). Notably, we detect a substantial expansion of the stem cell pool only when both pathways are simultaneously upregulated. In this co-overactivation state, follicle cells expand massively, do not differentiate, and instead retain a pFC-like character, suggesting that Hh activation induces differentiation only in the absence of active EGFR-Ras signaling. These hypertrophic pFCs display major hallmarks of cancer including a disrupted tissue architecture, a rampant cell cycle, and tissue overgrowth that is lethal for the host.

Results
EGFR-Ras and Hh signaling do not cross-regulate each other
The EGFR-Ras and Hh signaling pathway are both critical regulators of proliferation in the early follicle cell lineage19,23. To determine where these pathways overlap in the early FSC lineage, we made use of the Hh pathway reporter, Ptc-pelican, and an antibody detecting double phosphorylated ERK (dpERK), which reports active EGFR-Ras signaling. Consistent with the literature, both reporters displayed high activity in somatic cells in Regions 1 and 2 of the germarium (Fig. 1A–B)16,24. The dpERK signal was consistently present in cells at the Region 2a/b border, where FSCs reside, and sporadic in Regions 2b and 3. In contrast, Hh activity was detectable throughout the early FSC lineage from the Region 2a/2b border to Region 3 with gradually decreasing levels, as described previously. Thus, both pathways are consistently active at relatively high levels in FSCs, and exhibit different patterns of activity in pFCs.

Next, to investigate the effects of EGFR-Ras and Hh signaling we used the early follicle cell driver, 109-30-Gal425 and a temperature-sensitive Gal80 (109-30ts)26,27 to constitutively activate these pathways in the follicle epithelium specifically during adulthood. We expressed the wildtype Hh ligand to overactivate Hh signaling (HhOE)28 and a constitutively active allele of EGFR (EGFRλtop4.4, hereafter referred to as EGFRCA)29 to overactivate EGFR signaling. We also combined a constitutively active Ras allele (Ras85DV12, referred to as RasV12) with 109-30-Gal4 and Gal80ts as an additional method of activating the EGFR-Ras pathway30. In ovarioles with HhOE, large clusters of follicle cells accumulated between follicles and the follicles rarely progressed beyond the early stages of oogenesis (Fig. 1C–D). The remaining late stage follicle cells displayed irregular germ cell numbers and were often not fully encapsulated by an epithelial layer (Fig. 1D). Overexpression of EGFRCA resulted in a fusion of germline cysts with follicle cells evenly distributed on and in between cysts, and most ovarioles contained several mid- and late-stage follicles (Fig. 1E). In ovarioles with overexpression of RasV12, the normal structure of the ovariole was completely disrupted and follicles rarely formed at all (Fig. 1F).

To test for cross-regulation between EGFR-Ras and Hh signaling in the follicle epithelium we investigated the effects of overactivation on pathway reporters (Fig. 1G–J). We made use of a cherry-tagged Ptc construct, which accurately reflected Ptc-pelican expression in the germarium, but additionally displayed low activity levels in stalk and polar cells (Fig. 1G, Supplementary Fig. 1A–B). We noted that EGFR-Ras activity, monitored by dpERK staining, displayed occasional activity in MB cells, but was not observed in stalk cells (Fig. 1G, Supplementary Fig. 1C). Notably, MB cells in mitosis were positive for dpERK, consistent with a cell cycle dependent activation pattern (Supplementary Fig. 1C). Further, we detected the typical activation in posterior follicle cells starting at Stage 5 follicle cells31. HhOE resulted in a significant increase in Ptc-cherry activity, affecting stalk regions more strongly than regions with MB morphology but did not increase dpERK activity in stalk regions (Fig. 1H, K–L). Likewise, EGFR-Ras overactivation by EGFRCA or RasV12 resulted in a strong increase in dpERK signal across all follicle cell types but did not affect Ptc-cherry activity (Fig. 1I–L). Markedly, RasV12 had a substantially higher effect on dpERK levels than EGFRCA (Fig. 1L). These results indicate that Hh and EGFR-Ras signaling do not directly affect pathway output of each other in follicle cells.

To investigate this notion further, we leveraged UAS-transgenic lines to inhibit pathway activity. Expression of dominant negative ERK (ERKD334N)32 or RNAi-mediated depletion of Raf resulted in double-rowed stalks, while depletion of smo by two independent RNAi constructs caused cyst fusions (Fig. 1M–O, Supplementary Fig. 1D–G). Expression of dominant negative ERK or Raf-RNAi in the background of HhOE did not rescue the accumulation of supernumerary stalk cells or loss of MB follicle cells on late stage follicles (Fig. 1P–Q, Supplementary Fig. 1D, H), while depletion of smo restored normal ovariole morphology, although stalk morphology was still slightly abnormal either displaying fusions or double rowed morphology (Fig. 1R, Supplementary Fig. 1E, I). Genetic inhibition of EGFR-Ras signaling by expression of either Raf-RNAi or ERKD334N in the background of EGFRCA or RasV12 prevented cyst fusion completely, although most ovarioles displayed long or double-rowed stalks (Fig. 1S–T, V–W, Supplementary Fig. 1D, J, L). However, smo-RNAi did not restore fusion phenotypes induced by EGFRCA or RasV12 (Fig. 1U, X, Supplementary Fig. 1E, K, M). Together, our results show that the Hh and EGFR-Ras pathways do not directly interact in the regulation of differentiation in the early FSC lineage.

Aberrant EGFR-Ras and Hh signaling disturb differentiation
While loss- and reduction-of-function analyses of EGFR-Ras and Hh signaling established their necessity for follicle epithelial proliferation and differentiation, it is less well understood how spatial restriction of pathway activity affects follicle epithelial homeostasis. Hence, in order to identify cell-type specific effects of pathway overactivation, we performed single-cell RNA-sequencing in duplicate on ovaries with 109-30ts driven overexpression of either Hh or EGFRCA or 109-30ts crossed to w1118 as a wild type control (4 wild type/WT datasets in total), resulting in a total of 43,495 cells after applying standard quality control filters (Supplementary Fig. 2A–C, Supplementary Data 1). We merged and batch corrected the data, performed iterative, unsupervised clustering, and determined cluster identity in the wild type dataset using previously described markers (Fig. 2A–B, Supplementary Fig. 2D–F, Supplementary Data 2). The clustering agreed well with published cell atlases12,33–36, and the increased resolution that we gained by sequencing a larger number of cells provided several new insights. First, we were able to detect two distinct clusters of stalk cells rather than one, as previously reported12,33,34. Both clusters expressed high levels of the stalk cell markers, CG46339 and anterior open (aop) but the cells in one cluster had significantly higher expression of LaminC (LamC) than the other (Supplementary Fig. 2F). Staining of wild type ovaries showed that Aop is expressed from Region 3 in the germarium and is thus expressed from the earliest stage of stalk cell differentiation whereas LamC expression is weaker in the first stalk and stronger in later stalk cells (Supplementary Fig. 3A–B). Thus, the two stalk cell clusters represent a younger and more mature stalk cell population. Second, we identified a new marker, biniou (bin) that is specifically expressed in EC and FSC clusters (Supplementary Figs. 2F, 3C). To test this predicted expression pattern in vivo, we performed immunofluorescence staining of Bin and Fas3 in wild type ovarioles. Indeed, we observed strong expression in escort cells throughout Regions 1 and 2a, as well as in an average of 3.9 ± 0.57 (n=15) Fas3+ cells at the anterior edge of the Fas3 expression domain, where the FSCs reside (Supplementary Fig. 3D). These anterior-most Bin+/Fas3+ cells were placed in Layer 1, as defined in ref. 10, in 43% of cases and in Layer 2 in the remaining 57%. Lastly, we found that deadpan (dpn) marks the polar cell cluster (Supplementary Fig. 2F). Indeed, Dpn antibody staining reliably identifies polar cells in early cyst stages (Supplementary Fig. 3E).

To assess the effects that either signaling pathway had on each cell type, we performed differential abundance testing, which examines whether specific cell types or states are over- or underrepresented between conditions37. While effects on the FSC population were mild, we detected an increase in pFC and stalk cell populations which was particularly pronounced in the HhOE dataset (Fig. 2C, Supplementary Fig. 4A–C). At the same time, late stage MB populations were underrepresented. To determine whether this was associated with differentiation defects, we performed pseudotime analysis38 on clusters that we expect to be affected by the Gal4-UAS system with 109-30ts (FSC, pFC and stalk populations, polar cells and MB 2-5). When we placed these cells on a developmental pseudotime trajectory using Monocle339, we found that, in the HhOE dataset, pFCs mostly populated the stalk cell trajectory, resulting in a higher average pseudotime than their wild type counterparts (Fig. 2D–E, Supplementary Fig. 4D–E). In addition, in all overexpression datasets, most pronounced in RasV12, MB cells were located at an abnormally early point in the trajectory, decreasing the average pseudotime compared to wild type MB cells (Fig. 2D–E, Supplementary Fig. 4D–G). Further, we performed reference mapping to our wild type atlas to test the confidence values of each cell’s identity12,40. In the WT dataset the cluster identities from reference mapping largely reflected those produced by unsupervised clustering (Fig. 2F–G, Supplementary Fig. 4H). In contrast, a large portion of MB and polar cells from the HhOE dataset mapped differently, either as pFCs or stalk cells (Fig. 2F–G). Furthermore, although the algorithm identified a large percentage of stalk cells correctly it gave low confidence values to these assignments, suggesting that these mutant stalk cells did not have a completely wild type stalk cell transcriptional profile (Fig. 2G, Supplementary Fig. 4I). In the EGFRCA and RasV12 datasets reference mapping identified late MB stages that are distinct from the identities produced by unsupervised clustering, further highlighting the effects of these mutations on normal MB differentiation (Fig. 2F–G, Supplementary Fig. 4J–K). In addition, in the RasV12 dataset, a high number of MB cells were mapped as polar cells (Fig. 2F–G). However, immunostaining detected very few Dpn positive cells in RasV12 ovarioles, in contrast to EGFRCA ovarioles (Supplementary Fig. 5A–C). We also noted a downregulation of the polar cell transcripts dpn, upd1, upd3 and Fas3 in the RasV12 dataset, indicating that RasV12 polar cells do not possess a mature polar cell character (Supplementary Fig. 5D).

To test whether RasV12 indeed exerts effects on polar cells distinct from those induced by EGFRCA we examined polar cells further. Polar cell specific induction of EGFRCA using upd-Gal4 did not result in any morphological defects when compared to a wild type control (Supplementary Fig. 5E–F). In contrast, polar cell specific RasV12 expression significantly increased the number of polar cells per cluster and caused a double row stalk phenotype (Supplementary Fig. 5G–H). Polar cell specific expression of ERKD N or Raf-RNAi did not alter polar cell numbers, suggesting that the MAPK-pathway is not required to be active in polar cells for their differentiation (Supplementary Fig. 5H). However, we noted that RasV12 polar cells were occasionally mitotic (as indicated by staining for the mitotic marker, phospho-Histone H3), while we did not observe mitotic control and EGFRCA polar cells, in agreement with previous reports41 (Supplementary Fig. 5I–M). As induction of proliferation is a well-described effect of the EGFR-Ras pathway and in agreement with our analysis on the pathway reporter dpERK, we conclude that the RasV12 transgene induces MAPK signaling more effectively than EGFRCA, resulting in ectopic mitotic divisions of polar cells.

Hh signaling promotes a mixed transcriptional state
To understand the effects of the Hh signaling pathway on follicle cell differentiation in more detail, we focused on Hh specific target genes. Differential expression analysis revealed that Hh overactivation results in the misexpression of pFC specific transcripts in differentiated cell types, indicating that Hh overactivation delays differentiation (Fig. 3A, Supplementary Data 3). Further, polar and MB cells displayed reduced expression of cell-type specific markers, substantiating the delayed differentiation effect (Fig. 3A). Indeed, staining for the polar cell specific marker Dpn only identified few positive cells in late stages (Supplementary Fig. 6A–B). Lastly, we detected an upregulation of stalk cell specific transcripts across all cell types, which we confirmed by staining for the stalk cell markers Aop and LamC (Fig. 3A–B, Supplementary Fig. 6C–F). Therefore, Hh overactivation simultaneously promotes an undifferentiated cell fate and differentiation toward the stalk cell fate.

In the wild type germaria, undifferentiated follicle cells (FSCs and pFCs) co-express both eyes absent (eya) and castor (cas), while stalk and polar cells are cas+, eya– and MB cells are cas–, eya+ (Fig. 3A, C–D, Supplementary Fig. 6G). Consistent with previous studies14, overactivation of Hh resulted in cas+, eya+ cells, detectable in our single-cell analysis and by immunostaining (Fig. 3A, C–D, Supplementary Fig. 6H). Our bioinformatic analysis predicts that some cas+, eya+ cells in the HhOE condition are not pFCs but instead are a combination of MB cells that retain cas expression and stalk and polar cells that retain eya expression (Fig. 3A, C–D). Consistent with this, we detected LamC high, Eya+ cells, suggesting that these cells are stalk cells that retain eya expression (Fig. 3E–F). Moreover, SCENIC analysis revealed that the activity of the transcription factor Zfh1 was strongly increased upon Hh overactivation (Fig. 3G–H, Supplementary Data 4) and immunostaining confirmed that while Zfh1 expression was limited to FSCs, pFCs and stalk cells in control ovarioles, somatic Hh overactivation cells were Zfh1 positive (Fig. 3I–J). Indeed, overexpression of Zfh1 resulted in supernumerary stalk cells, while depletion of zfh1 resulted in cyst fusions, suggesting that Zfh1 promotes the stalk cell fate (Fig. 3K–O). To test the role of zfh1 induction in the Hh overactivation phenotype, we depleted zfh1 in the background of HhOE. Indeed, zfh1 knockdown rescued the long stalk induced by Hh overactivation and even restored wild type morphology in some ovarioles, whereas it did not rescue EGFRCA or RasV12 phenotypes (Fig. 3P–Q, Supplementary Fig. 6I-U). This indicates that zfh1 is one of the major target genes induced by Hh signaling in the early FSC lineage.

Ectopic Hh signaling induces EMT
The mammalian Zfh1 orthologs ZEB1/2 are well known inducers of epithelial-to-mesenchymal transition (EMT) and play a major role in partial EMT-hybrid states observed during cancer metastasis. As the partial pFC/stalk cell fate induced by Hh overactivation in follicle cells resembles this transcriptional hybrid state, we hypothesized that Zfh1 promotes similar processes in follicle cell differentiation. To test this, we investigated whether Hh overactivation also promotes EMT in follicle cells. Indeed, we observed an upregulation of the EMT markers pebble (pbl) and heartless (htl) both by bioinformatic analysis as well as by analysing reporter lines expressing GFP-tagged Pbl or Htl under their endogenous promoters (Fig. 4A-F). EMT is associated with a loss of cell polarity. Hence, we tested the localization of the apical polarity determinant Bazooka (Baz/Par3) and the basolateral marker Discs-large 1 (Dlg1). While wild type MB cells displayed apical Baz and basolateral Dlg1 localization, as previously described42, HhOE MB cells often displayed a mislocalization or loss of polarity markers, associated with a flattened morphology (Fig. 4G-I). Next, we investigated the effects of HhOE on stalk cell polarity. The stalk cells undergo intercalation from a double layered epithelium to a single row of cells. This intercalation process depends on the reorganization of cell polarity, adherens junctions and actin remodeling43. Prior to intercalation, stalk cells form a double row of cells with apical membrane portions, marked by Baz, facing each other, while the lateral membrane marker Dlg1 is restrained from apical surfaces (Fig. 4J). HhOE stalk cells failed to establish an neatly organized apical membrane domain. Instead, apical areas were disorganized and showed ectopic localization of Dlg1 (Fig. 4K).

Another hallmark of EMT is cell motility and, indeed, Hh overactivated stalk cells displayed strong enrichment of F-actin, marked by Phalloidin staining (Fig. 4K). Live imaging of control and HhOE ovarioles revealed that follicle cells overexpressing Hh display irregular motility (Supplementary Movies 1–3). As with wild type stalk cells, HhOE stalk cells intercalate from a double row into a single row (Fig. 4L–M, Supplementary Movies 1-2). However, HhOE stalk cells do not remain intercalated but instead moved further, progressing back into a double row state (Fig. 4M, Supplementary Movies 1–2).

We further noted altered MB cell motility upon Hh overexpression (Fig. 4N–O, Supplementary Movie 3). Wild type MB cells undergo a collective migration known as follicle cell rotation, where MB cells move around the germ cell cyst to organize the extracellular matrix and promote egg chamber elongation44,45. HhOE MB cells rotated normally, but also displayed invasive migration toward the germ cell cyst (Fig. 4N–O, Supplementary Movie 3). Late stage HhOE follicles often contained too few germ cell nuclei (Fig. 4P). Further, advanced cysts regularly display areas where germ cells are separated from each other by stalk-like regions (Fig. 4P), suggesting that HhOE MB cells migrate into germ cell cysts and form stalk-like regions that separate germ cells from each other.

In the WT dataset, we detected the highest expression of pbl and htl in stalk cells (Supplementary Fig. 6V). This suggests that, in wild type cells, Hh signaling induces a short pulse of partial EMT in early stalk cells or stalk-cell fated pFCs that promotes the remodeling of cell polarity, allowing them to intercalate. Sustained Hh activity, however, prevents stalk cells from the timely exit of intercalation, maintaining them in a continuous state of intercalation movements.

Activation of proliferation disturbs differentiation
Our analysis of regulon activity revealed that the activity of two transcription factors that are known to regulate proliferation, Pointed (Pnt) and the E2F transcription factor 1 (E2f1)46,47, is increased in EGFRCA, RasV12 and HhOE conditions (Fig. 5A–B, Supplementary Data 4–6). As the Hh and EGFR-Ras pathways are both prominent regulators of proliferation in the early follicle cell lineage9,16–18, we investigated the effects of these transcription factors on the cell cycle in more depth. Notably, we did not detect any effects on E2f1 RNA expression levels in either genotype, whereas RasV12 had a strong effect and EGFRCA had a mild effect on pnt RNA expression levels (Fig. 5C). Interestingly, overexpression of E2f1 and its partner Dp or Pnt resulted in prominent fusions of cysts resembling the EGFRCA overexpression phenotype (Figs. 1E, 5D-F, Supplementary Fig. 7A). E2f1 is a well-known cell cycle regulator required for G1 to S transition and Pnt induces cell cycle related genes during neural development and is induced by Ras signaling46–48. This strongly suggests that increased proliferation is a major driver of the phenotype observed upon EGFR-Ras overactivation.

To test this hypothesis further, we examined the expression of known cell cycle specific genes in our dataset to determine the cell cycle phase for each cell (Fig. 5G-H, Supplementary Data 7). We found that follicle cells are primarily in G2 phase during mitotic stages up to Stage 5, and switch to primarily G1 phase from Stage 6 onwards, at which point MB cells start endocycling (Fig. 5G-H)49–51. Stalk and polar cells, which are post mitotic, were predicted to arrest in G241,52. Indeed, antibody staining for the mitotic marker phospho-Histone H3 (Ser10) detected wild type follicle cells in mitosis until Stage 5, as defined by the nuclear size of nurse cells53 (Fig. 5I). Stalk cells, polar cells and MB cells in later stages were phospho-Histone H3 negative in WT ovarioles. Additionally, we assayed for the cell cycle phase using a CycB-nls-RFP construct, which allows for discrimination between G1 cells (RFP–) and S/G2/M cells (RFP+)54. The majority of follicle cells in the germarium, stalk cells, and polar cells exhibited strong nuclear RFP signal (Supplementary Fig. 7B) whereas MB cells from Stage 2-5 were only occasionally positive and expressed lower levels of CycB-nls-RFP. MB cells from Stage 6 onwards were CycB-nls-RFP negative (Supplementary Fig. 7B-C), indicating that endocycling MB cells are mostly in G1-phase. Cell cycle scoring results showed that WT cells in the MB 2-5 cluster are mostly in G2M phase while WT cells in the clusters containing Stage 5-6 MB cells are increasingly more likely to be in G1 phase (Fig. 5G). We investigated the expression of cell cycle specific genes (polo, aurB and Det for M-phase; stg, CycA and CycB for G2 and Cdk1, CycD and CycE for G1) as described55, and found that WT mitotic MB cells expressed high levels of G1, G2 and M phase genes in Stages 2-5, and then downregulated G2 and M phase genes from Stage 6 onward, as expected (Fig. 5H). In comparison, the level of G2 genes did not decrease as much in mid- to late-stage HhOE MB cells (Fig. 5G). Consistent with this, we detected mitotic cells associated with cyst stages beyond Stage 5 in HhOE MB cells (Fig. 5J). Further, most cells retained high levels of CycB-nls-RFP (Supplementary Fig. 7E). In the EGFRCA and RasV12 conditions, G2 gene expression remained very high in mid-stage MB cells and MB cells in Stage 6 follicles or later were frequently phospho-Histone H3+ and CycB-nls-RFP+ (Fig. 5G, K-L, Supplementary Fig. 7C, F-G).

We tested whether E2f1 or Pnt induce ectopic mitosis by investigating ovarioles with the respective overexpression. While E2f1 and Dp overexpression displayed no mitotic cells beyond Stage 6, ovarioles with Pnt overexpression contained mitotic cells across all stages, suggesting that Pnt is a key target of the EGFR-Ras pathway in the regulation of the MB cell cycle (Fig. 5M-O). To test this, we depleted pnt by RNAi, which resulted in egg chamber fusions without a follicle epithelium separating the fused cysts, in agreement with an insufficient production of follicle cells (Fig. 5P–Q). Depletion of pnt did not rescue the formation of an extensive stalk in HhOE ovarioles but resulted in a partial rescue of the EGFRCA and RasV12 phenotypes (Fig. 5R-X). However, pnt-RNAi could not restore fusion and stalk morphology defects entirely. Additionally, ovarioles still displayed ectopic mitosis in MB follicle cells associated with cysts later than Stage 5 (Supplementary Fig. 7H–J). Hence, pnt is one, but likely not the only, important target of EGFR-Ras signaling in this process.

Next, we examined the expression of genes known to regulate the switch to endocycling, including string (stg), which is downregulated, and fizzy-related (fzr), which is upregulated to facilitate the exit from mitotic cell cycle56. While the expected expression changes of stg and fzr occurred in wild type MB populations, the HhOE, EGFRCA and RasV12 MB populations maintained stg expression and failed to upregulate fzr in later MB fates (Fig. 5Y), suggesting that activation of these pro-proliferative signaling pathways blocks the mitotic to endocycle switch. Studies of embryonic stem cells showed that a long G1 phase renders cells susceptible to differentiation57–59. We hypothesized that the reduction of late stage MB follicle cell populations we observed upon pathway activation (Fig. 2C) is caused by a failure of MB cells to differentiate properly. Indeed, MB populations with Hh or EGFR-Ras overactivation retain markers for early MB populations like CG15546, CG31808 and SPARC and fail to upregulate markers of MB differentiation including mirr, bond, CG8303, Yp2, psd, Vml and dpp (Fig. 5Y)12,33,34.

To investigate this further, we examined two markers of MB differentiation by immunostaining. First, we found that WT MB cells downregulate Eya shortly after exiting mitosis in Stage 6 (Supplementary Fig. 8A) whereas many HhOE cells retain Eya expression throughout mid-oogenesis (Supplementary Fig. 8B). In the EGFRCA and RasV12 conditions, Eya expression decreased after a point in mid-oogenesis, similar to the WT condition, suggesting that the MBs in these mutant ovaries can progress past Stage 6. However, unlike in the WT and HhOE conditions, many Eya– EGFRCA or RasV12 MB cells were still mitotic, as indicated by staining for phospho-Histone H3 (Supplementary Fig. 8C-E). Second, we examined the expression of BrC, which is upregulated in WT MB cells slightly before the entry to endocycling (Supplementary Fig. 8F). HhOE MB cells express BrC in occasional cases (Supplementary Fig. 8G). In EGFRCA and RasV12 ovarioles we detected mitotic cells in late Stages expressing high levels of BrC (Supplementary Fig. 8H-I). Together, these results suggest that the ectopic mitosis induced by HhOE is caused by a delay in differentiation that prevents MB cells from reaching the stage of differentiation where they would undergo the mitotic to endocycle switch whereas the ectopic mitosis induced by EGFRCA and RasV12 expression is due to a failure of MB cells that have reached this stage, to exit mitosis.

Distinct growth modes prevent hyperplasia
While we detected strong defects in follicle cell differentiation, differential abundance testing did not predict a large increase in the number of FSCs (Fig. 2C). To test this further, we used immunofluorescence to assay for FSC numbers in ovaries with overactivation of EGFR-Ras, Hh, or related signaling pathways. In agreement with bioinformatic predictions, we did not detect significant changes in the number of FSCs, marked by Bin and Fas3 co-expression, in EGFRCA and RasV12 ovarioles (Fig. 6A). HhOE increased FSC numbers two-fold to 8.2 ± 1.08 cells (n=14, p=0.0022 by student’s t-test) (Fig. 6A). As EGFR-Ras signaling is induced by the Wnt pathway in FSCs, we tested the effect of expressing a constitutively active β-Catenin allele, ArmS10, which increased FSC numbers by two-fold (Fig. 6A). Likewise, since Hh signaling promotes proliferation via the Hippo pathway effector yorkie, we tested the effect of overexpressing a constitutively active allele of Yorkie (Yki3SA), which did not have significant effects on FSC numbers (Fig. 6A). Next, we tested whether co-overactivation of pathways with known interactions had substantial effects on FSC numbers. Neither co-expression of ArmS10 with EGFRCA nor of HhOE with Yki3SA increased FSC numbers beyond the increase observed by single overexpressions alone (Fig. 6A). In contrast, co-overactivation of the Hh pathway with either ArmS10, EGFRCA or RasV12 significantly increased FSC numbers well beyond additive effects of single overactivations (Fig. 6A–D, Supplementary Fig. 9A). Thus, independent regulation of proliferative signals protects against excessive stem cell pool expansion in the event of aberrant pathway activation.

To further investigate the effects of co-overactivation of non-interacting pathways we examined the consequences of HhOE-EGFRCA and HhOE-RasV12 co-expression on follicle cell number and tissue morphology. In contrast to all other genotypes, these genetic manipulations caused a rapid expansion of cells which grew into large masses that contained few germ cell cysts (Fig. 6E, Supplementary Fig. 9B–J). We stained for markers of differentiation and found that most cells expressed Zfh1, Eya and no or very few expressed the stalk cell marker LamC (Fig. 6F–K). These cells did not induce the expression of BrC, a marker of Stage 6 MB cells, except in very rare cases (Supplementary Fig. 9K–L). This suggests that cells retain a differentiation fate similar to pFCs, which express this marker combination in wild type ovarioles.

Our previous results demonstrated that limited marker numbers do not reliably identify cell fate. We therefore performed single-cell RNA-sequencing of ovarioles with HhOE-EGFRCA and HhOE-RasV12 expression and a matched control in duplicates after induction for 5 days. We sequenced a total of 20,985 high quality cells and analysed the dataset together with our previous dataset to allow for comparison (Fig. 6L, Supplementary Fig. 10A-C, Supplementary Data 8). This control (hereafter WT 5d) dataset displayed similar clusters, marker expression, pseudotime trajectory and reference mapping result as the previous WT control (hereafter WT 14d) (Fig. 6M-P, Supplementary Fig. 10D-H, Supplementary Data 9). In contrast, in both co-overexpression conditions, differential abundance testing identified a strong increase of the pFC state and the earliest MB cell fate (MB 2-5) (Fig. 6N, Supplementary Fig. 10I). Additionally, reference mapping predicted the overwhelming majority of cells as pFCs and pseudotime analysis placed the cells at the beginning of pseudotime (Fig. 6M, O-P, Supplementary Fig. 10F-I), confirming that co-overactivation of Hh and EGFR-Ras signaling indeed promotes a massive expansion of the pFC pool.

To test whether pFCs indeed give rise to this expansion of cells, we made use of Gal4 driver lines12,60 targeting distinct follicle cell populations to express HhOE with either EGFRCA or RasV12 (Supplementary Fig. 11A–F). We found that only Gal4 drivers with expression in MB cells caused tumor-like growth (Supplementary Fig. 11G-N). This demonstrates that the aberrant expansion of Hh-EGFR/Ras cells is likely caused by MB follicle cells retaining pFC character. This conclusion is, however, limited by the specificity of the applied Gal4-driver tools. Together, our results show that proliferation control by non-interacting pathways can protect from pathway deregulation. Further, we identified Hh-EGFR/Ras co-overactivation as a particularly potent inducer of undifferentiated cell expansion.

Co-activation of Hh and EGFR-Ras signaling aids malignancy
In the Gal80-Gal4-UAS system used in this study, transgene expression is induced by a temperature shift of newly hatched adults from the restrictive 18°C to the permissive 29°C temperature. At 18°C the temperature sensitive Gal80 inhibits expression of UAS-transgenes by Gal4. At 29°C Gal80 is inactive, allowing for the induction of transgene expression. In standard experimental procedures, we allow for transgene expression for 14 days, after which morphological phenotypes are easily dissectible. When we applied these standard procedures to Hh-EGFRCA/RasV12 co-expression, we could not recover any females. We noted that females of the desired genotype indeed hatched, however, they rapidly died after temperature shift (Fig. 7A). In contrast, males of the same genotype or males and females from control and single overactivations did not display increased lethality over the observed timeframe (Fig. 7A). This suggests that co-overactivation of Hh and EGFRCA or RasV12 resulted in lethal tumor-like growth. To better dissect phenotype progression, we investigated ovarioles at distinct time points after induction. We found that pathway activity reached its maximum at Day 3 in agreement with Gal4 system activation and remained steady at Day 6 (Supplementary Fig. 12). Throughout this time period, morphological phenotypes worsened progressively, suggesting that the pFC population expands rapidly after transgene induction.

Based on these observations, we next investigated whether co-overactivated Hh-EGFR/Ras follicle cells exhibit other hallmarks of cancer. Indeed, we discovered that Hh-EGFR/Ras follicle cells display strong expression of the EMT marker Pbl and Htl as well as a loss of apical-basal polarity (Fig. 7B-J). In addition, we found that cancer-associated genes involved in tissue architecture, such as actin cytoskeleton and cell adhesion regulators, and metabolic regulation, such as Mondo and Adgf-A, were dysregulated in both malignant genotypes (Fig. 7K, Supplementary Data 10–11). Further, we detected an upregulation of Thor and other genes responding to cancer-associated stress conditions (Fig. 7K).

In addition, Hh-EGFR/Ras overactivation substantially dysregulated proliferation. Follicle cells with Hh-EGFR/Ras overexpression displayed mitotic cells throughout the tissue and retained high levels of CycB-mRFP-nls expression (Fig. 7L-O). Moreover, our bioinformatic analysis suggested that cells with co-overactivation of Hh and EGFR-Ras do not undergo the switch from primarily G2M to primarily G1 (Supplementary Fig. 13A). Indeed, we detected phospho-Histone H3 and CycB-nls-RFP positive cells throughout these mutant ovarioles (Fig. 7L-O). Quantification of CycB-nls-RFP negative G1-phase cells revealed that less than ten percent of cells in the co-overactivations were in G1, compared to roughly forty percent of Region 2b WT cells (Fig. 7P-S), suggesting an accelerated cell cycle. We surveyed the expression of a distinct set of cell cycle specific genes55 (polo, aurB and Det for M-phase; stg, CycA and CycB for G2 and Cdk1, CycD and CycE for G1) in Gal4-expressing clusters. WT cells expressed high levels of G1 and G2 genes and low levels of M-genes, as expected for long gap phases and short mitotic phases (Supplementary Fig. 13B). In contrast, a larger portion of cells in both co-overexpression conditions expressed M-phase specific genes. In particular, stg was strongly upregulated in both co-overactivations samples (Supplementary Fig. 13C-D). Thus, co-overactivation of Hh and EGFR-Ras signaling promotes sustained mitotic cell cycle progression.

Lastly, we asked whether Zfh1 and Pnt, which we identified as relevant target genes of Hh and EGFR-Ras signaling respectively, are relevant for malignant growth. We found that depletion of zfh1 in the co-overactivation background restored tissue morphology to a state that is similar to expression of either EGFRCA or RasV12 alone (Fig. 7T-U, Supplementary Fig. 13F). Next, we depleted pnt, which partially restored the morphology with less severe overgrowth allowing some large cysts to form. However, pnt depletion did not restore the HhOE phenotype, consistent with our conclusion that pnt is not the only relevant target gene of EGFR-Ras signaling (Fig. 7V-W, Supplementary Fig. 13F). Together, our findings indicate that co-overexpression of the Hh and EGFR-Ras pathways promote tumor-like growth that exhibit several hallmarks of cancer, including rapid growth, altered tissue architecture, a dysregulated cell cycle and reduced viability of the tumor host.

Methods
Fly husbandry
Flies were reared at 18°C and newly hatched adults were shifted to 29°C and fed wet yeast daily until dissection. Flies were dissected 14 days after the temperature shift if possible. As the double overactivation of HhOE and EGFRCA or HhOE and RasV12 were lethal at 14 days, we dissected after 5 days instead and paired each experiment with a respective control.

The following Drosophila melanogaster stocks were used:
BDSC: tub-Gal80ts: #7108 and #7017, 109-30-Gal4: #7023, ptc-mCherry: #86272, UAS-smo-RNAi #1: #27937, UAS-smo-RNAi #2: #62987, Pbl-GFP: #59839, Wnt4-Gal4: #67449, stl-Gal4: #77732, CG46339-Gal4: #77710, w1118: #3605, UAS-ArmS10: #4782, UAS-Ras85DV12: #64196, UAS-Hh::EGFP: #81024, UAS-YkiS111A.S168A.S250A: #28817, UAS-Pnt.P1: #869, UAS-Pnt.P2: #399, UAS-E2f1, UAS-Dp: #4770, UAS-Zfh1: #6879, UAS-zfh1-RNAi #3: #29347, CycB-nls-mRFP: #55124. VDRC: UAS-Raf-RNAi: #107766, Htl-GFP #318120, UAS-zfh1-RNAi #1: #42856, UAS-zfh1-RNAi #2: 103205, UAS-pnt-RNAi: #7170. The following lines were kindly gifted as indicated: Ptc-pelican (T. Kornberg, UCSF, San Francisco), upd1-Gal4;;tub-Gal80ts (D. Montell, UCSB, Santa Barbara), UAS-EGFRλtop4.4 (T. Schüpbach, Princeton University, Princeton), zfh1-Gal4 (60, C. Bökel, University Ulm), DE-Cad::mTomato (85, A. Wodarz, University Cologne), UAS-ERKD334N (32, M. Wolf, Duke University).

Immunofluorescence staining and imaging
Ovaries of adult flies were dissected at RT in PBS and fixed for 20 min at RT with 4% PFA. The tissue was washed twice for 10 min in PBS and blocked for 30 min in blocking buffer (PBS with 0.2% Triton X-100 and 0.5% BSA). Incubation with primary antibody diluted in blocking buffer was performed overnight at 4°C. On the following day, ovaries were washed three times for 10 min in blocking buffer and incubated for 2–4 h at RT with secondary antibody diluted in blocking buffer. After washing the ovaries 3 times for 10 min with blocking buffer, samples were rinsed with PBS and mounted in DAPI Fluoromount-G (Thermo Fisher Scientific, OB010020). Imaging was performed with a Leica TCS SP8 with an HC PL APO CS2 63x/1.4 oil objective and Leica Application Suite X (LasX, Version 3.5.2.18963). Images were processed with FIJI v2.1.0/1.53c86 and figures prepared in Inkscape 1.0.2 (e86c8708, 2021-01-15).

The following antibodies were used:
DSHB: mouse anti-Fas3 (7G10, 1:100), mouse anti-Aop (8B12H9, 1:100), mouse anti-LamC (LC28.26, 1:100), mouse anti-Eya (10H6, 1:50), rat anti-ECad (DCAD2, 1:100), mouse anti-Dlg1 (DLG1, 1:100).
rabbit anti-GFP D5.1 (Cell Signaling #2956, 1:1000), rabbit anti-dpERK (Cell Signaling #4370, 1:100), rat anti-Dpn (abcam ab195173, 1:100), rabbit anti-Bin (gift from M. Frasch, 1:200), rabbit anti-Zfh1 (gift from J. Skeath, 1:500), rabbit anti-Cas (gift from W. Odenwald, 1:1000), mouse anti-GFP JL-8 (Takara Bio 632380, 1:1000), rabbit anti-pH3 (Sigma-Aldrich #06-570, 1:500), rabbit anti-Baz (gift from A. Wodarz, 1:1000).

Secondary antibodies were purchased from Invitrogen and applied in a 1:1000 dilution: goat anti-mouse 488 (A-11029), goat anti-mouse 568 (A-11031), goat anti-rabbit 488 (A-11034), goat anti-rabbit 568 (A-11036), goat anti-rat 488 (A-11073), goat anti-rat 568 (A-11077), goat anti-rat 647 (A-21247).

Live imaging
Ovarioles were dissected in Schneider++ medium with 0.2 mg/mL Insulin (Sigma-Aldrich I9278) embedded in Schneider++ with 0.2 mg/mL Insulin and 0.5% low melting agarose in an imaging chamber (Ibidi 80806). Imaging was performed with a Leica TCS SP8 with an HC PL APO CS2 63x/1.4 oil objective and Leica Application Suite X (LasX, Version 3.5.2.18963) every 10 minutes and videos processed with processed with FIJI v2.1.0/1.53c86.

Single-cell RNA-sequencing
Each genotype was sequenced in duplicates with a matched wild type control. Single-cell solutions were prepared from a pool of circa 60 adult ovaries per replicate following established protocols12. Prior to dissection, newly hatched females were cultured at appropriate conditions with supply of wet yeast. Ovaries were then dissected on ice in Schneider’s Insect Medium with 10% FBS and 167 mg/mL insulin within a maximum of 45 min. During dissection we enriched for non-vitellogenic stages using micro-scissors where phenotypes allowed for it. Ovaries were rinsed with ice cold Cell Dissociation Buffer (Thermo Fisher Scientific 13141014) and dissociated in Cell Dissociation Buffer with 4 mg/mL elastase (Worthington Biochemical LS002292) and 2.5 mg/mL collagenase (Invitrogen # 17018-029) for 20 min at RT under constant pipetting to promote dissociation. Samples were filtered through a 50 µM filter and dissociated for another 10 min prior to filtering through a 30 µM filter. After addition of 500 µL Schneider’s Insect Medium with 10% FBS and 167 mg/mL insulin the solution was centrifuged for 5 min at 4°C and 3500 rcf and the pellet washed with Schneider’s Insect Medium with 10% FBS and 167 mg/mL insulin. After an additional pelleting and washing step the pellet was resuspended in PBS with 0.04% ultrapure BSA (Thermo Fisher Scientific AM2616) and cell concentration adjusted to 1000 cells per µL. Libraries were generated using the Chromium Single-Cell 3’ Reagent Version 2 Kit (10× Genomics) for dataset 1 and the Chromium Next GEM Single-Cell 3´ LT Kit v3.1 (10× Genomics) for dataset 2. Sequencing was performed on Illumina HiSeq 2500 for dataset 1 and NovaSeq 6000 for dataset 2 according to the respective 10× Genomics manual.

Bioinformatic analysis
For dataset 1 reads were aligned to the Drosophila reference genome (dmel_r6.19) using STAR v2.5.1b87 and resulting bam files were processed with Cell Ranger 4.0.0. For dataset 2 we aligned to dmel_r6.19 using STAR Solo88. Post-processing was performed with Seurat 5.3.1 using R 2022.0740. We filtered out low quality cells based on the number of detected genes and percent of mitochondrial reads. Both datasets were merged and batch corrected using Seurat. Unsupervised clustering was performed with Seurat in iterative cycles with resolution factors noted in Supplementary Fig. 2E and clusters annotated by marker expression. Differential gene expression was analysed using the FindAllMarkers() and FindMarkers() commands from the Seurat package. Genotype specific gene expression was analysed in comparison to the respective matched control. Reference mapping was performed with the wild type dataset published in ref. 12 using Seurat. Pseudotime was calculated using Monocle3 1.4.2639 with standard settings and after batch correction as described in ref. 89. Regulons of the WT datasets from dataset 1 were determined using SCENIC 1.3.1 and the cisTarget v8 motif collection mc8nr90. Regulon activity was then determined across genotypes using the PercentageFeatureSet() command of Seurat. Differential abundance was tested using miloR BioC 3.2237. Scales in Seurat expression plots and maps display the expression in log((UMI+1/total UMI) × 104).

Statistics and reproducibility
Statistical analyses were performed with R 2022.07. We tested for data distribution using the Shapiro–Wilk test and then applied two-tailed student’s t-test for parametric and the Kruskal–Wallis test for non-parametric samples. Bonferroni corrections were conducted were mandated as described in the figure legends. No statistical method was used to predetermine sample size. Graphs were plotted in R. All images and quantifications are representative of at least three independent experiments. Single-cell datasets were performed in duplicates with matched wild type controls. For dataset 1 a total of four and for dataset 2 a total of 2 wild type controls were performed. No data were excluded from the analyses and the experiments were not randomized. Quantitative microscopy of the Drosophila ovary are representative of at least three independent experiments.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "Reviewer Comments on “A single-cell analysis of Hh and EGFR-Ras: Independent signaling pathways prevent tumorigenesis”\nRust et al. present a technically sophisticated study combining genetic perturbation and single-cell transcriptomics to explore how Hh and EGFR-Ras signaling affect cell fate and proliferation in the Drosophila follicle epithelium. The authors identify transcriptional hybrid states, altered cell cycle control, and overgrowth phenotypes under pathway co-activation, which they interpret as hallmarks of tumorigenesis. While the dataset is rich and the experimental system well-chosen, the study’s interpretive clarity and mechanistic depth are hampered by key conceptual, analytical, and structural weaknesses.\nMajor Points\n1. The manuscript suffers from a lack of a clear conceptual thread. The experimental flow often feels observational rather than hypothesis-driven, with new datasets introduced without clear rationale. This impairs readability and interpretability, even for domain experts. To improve clarity and engagement, the authors should reorganize the results around discrete, testable questions and explicitly state the purpose of each experimental step.\n2. The assertion that Hh and EGFR-Ras function independently is not supported by mechanistic data. The pathways converge on shared transcriptional targets and exhibit synergistic phenotypes. Without epistasis experiments or systematic pathway activity measurements (e.g., ptc-GFP, dpERK) in single vs. double mutant backgrounds, “independent” is an overstatement. The term “functionally parallel” would be more appropriate unless cross-regulation is explicitly ruled out.\n3. Despite generating a large and high-quality scRNA-seq dataset, the analysis remains descriptive. No trajectory inference or fate-mapping is performed, even though the central claims revolve around hybrid states and differentiation arrest. Methods such as Monocle 3, Palantir, or scVelo could clarify whether mutant cells deviate from canonical lineage trajectories or are blocked at specific transitions.\n4. While the co-activation phenotypes resemble dysplasia, the study lacks definitive lineage tracing or clonal analysis to establish tumor origin and progression. The use of broad drivers (e.g., 109-30-Gal4) precludes spatial or temporal precision. Tools such as MARCM, G-TRACE, or temporally restricted Gal80ts could strengthen the argument for cell-autonomous tumor initiation. Furthermore, quantitative assessment of rescue phenotypes (e.g., zfh1-RNAi, pnt-RNAi) remains incomplete.\n5. The conclusion that Hh induces EMT is based solely on transcriptional upregulation of EMT-associated genes. No morphological or functional evidence of EMT, such as polarity loss, cell delamination, or motility, is provided. Immunostaining for polarity markers (e.g., Crb, aPKC), adhesion molecules, and cytoskeletal organization should be used to validate this claim. Without such data, “EMT-like transcriptional state” is the appropriate framing.\n6. Mutant cell clusters map poorly to wild-type references, raising concerns about misclassification. Marker misexpression could mimic FSC/pFC expansion. The origin of the tumor-like overgrowth remains unclear. Additional immunostaining, co-expression validation, and lineage tracing are necessary to support the conclusion that tumors arise from pFCs.\n7. The authors repeatedly refer to a “hybrid state” to describe cells that co-express markers of both undifferentiated and differentiated follicle cell fates. However, the term “hybrid state” has specific connotations in developmental and cancer biology, typically implying a stable or metastable identity with functional consequences, such as altered plasticity, lineage potential, or behavior. In this study, the designation appears to be based solely on transcriptional co-expression, without supporting evidence for functional hybridity or trajectory disruption. The authors should therefore define more precisely what they mean by “hybrid,” clarify whether this is a transient, transcriptional, or functionally stable state, and consider using a more neutral term (e.g., “mixed transcriptional profile”) unless further dynamic or functional validation is provided.\n8. The manuscript surveys several signaling pathways (Wnt, JNK, Hippo), but the main mechanistic insights and tumorigenic phenotypes stem from Hh and EGFR-Ras overactivation. Including additional pathways without comparable depth or functional relevance diffuses the narrative and dilutes the manuscript's impact. The authors should consider narrowing their focus to the Hh and EGFR-Ras axis—which clearly drives the key phenotypes—or explicitly justify the inclusion of other pathways with targeted analyses or integrative comparisons. This would greatly enhance conceptual coherence and mechanistic clarity.\nAdditional comments:\n- The manuscript includes limited pH3 staining to show persistence of mitotic cells beyond stage 6 in EGFR or Ras overactivation conditions, supporting disruption of the mitosis-to-endocycle transition. However, this analysis is qualitative, not systematically quantified across genotypes, and is not extended to the double mutant tumor contexts where cell cycle misregulation is central to the conclusions. Moreover, other key claims, such as accelerated cycling, checkpoint evasion, and altered G1/G2 phase dynamics, are based entirely on transcriptomic inference. These would be significantly strengthened by incorporating functional assays such as EdU/BrdU incorporation for S-phase entry, FACS-based DNA content profiling, and broader use of mitotic and G2/M markers. This would provide crucial validation for the computational predictions and enhance the mechanistic rigor of the study.\n- While Gal80ts permits temporal control, the kinetics of tumor initiation and transcriptional changes remain unresolved. A time-course analysis (e.g., staged scRNA-seq or live imaging of pathway reporters) could clarify the sequence and causality of key phenotypic transitions.\n- Reference mapping to wild-type atlases is used to support hybrid or misclassified cell identities, but mapping confidence metrics (e.g., Seurat prediction scores or LISI values) are not reported. Including these would improve interpretability and lend quantitative support to claims of lineage disruption.\nMinor Points\n• Figures are fragmented and key data (e.g., double mutant phenotypes) are scattered; consolidation would aid comprehension.\n• Statistical reporting is inconsistent. All n-values and p-values should be included; bar graphs should be replaced with dot/violin plots.\n• Methodological transparency should be improved. Full computational parameters and code (e.g., for SCENIC, Milo, batch correction) should be shared via GitHub or Zenodo.\n• Terminology such as “tumor and “independent” should be used with greater precision and caution.\n• The discussion of parallels with human cancer should be grounded in conserved pathway logic (e.g., Zfh1/ZEB1, Pnt/ETS) rather than speculation.\nConclusion\nThis study addresses important questions in epithelial plasticity and oncogenic signaling using a powerful model and modern transcriptomic tools. However, its impact is undermined by conceptual overreach, narrative disorganization, and a lack of mechanistic validation. Major revisions, including trajectory inference, targeted rescue and epistasis experiments, lineage tracing, and clarification of experimental logic, are necessary to realize the full potential of this work. With these improvements, the manuscript would make a valuable contribution to the field.", "reviewer_2": "The authors use the follicular epithelium of the Drosophila ovary to address the contribution of different signaling pathways to cell proliferation and differentiation. They first combine overexpression of the Hh ligand and/or constitutively activated EGFR and Ras1 with single-cell transcriptomics to define the transcriptional profiles of the affected follicular cells. They are able to define several cell clusters based in their transcriptomic profiles, identifying differentially expressed genes downstream of the affected signaling pathways. They also analyze combined over-activation of the same pathways, and identify a highly proliferative phenotype of undifferentiated cells accompanied by novel transcriptomic signatures. Finally, the authors also do a comprehensible phenotypic description of the consequences of their genetic manipulations, as well as epistatic analysis to better define the key components of Hh, EGFR and other signalling pathways involved in the assignation of cell states.\nThis seems to me as a very significant and timely analysis in which a lot of effort has been put into the comparison between transcriptomic signatures, the action of candidate signaling pathways and the identification of the main components of these pathways through functional genetic analysis. The methodology is aligned with the standards of the field, the description of the results accurate and in my view the results support the many conclusions stated in the manuscript. I am not expert in the bioinformatic processing of single cell sequencing experiments, and consequently I cannot express a knowledgeable opinion on methods, methodology and data analyses.\nIn summary, I consider the manuscript a valuable contribution in the fields of cell signaling, cell signaling pathways interactions, regulation of cell differentiation and proliferation and cooperative effects promoting tumoral development that will be of interest to a variety of scientist working in these and related areas, and I am quite happy to recommend its publication. To me the strongest points are: 1) identification of the main components mediating the action of the Hh (zfh1) and EGFR (pointed) signaling pathways, 2) identification of cooperativity in the regulation of gene expression in response to these pathways, 3) critical contribution of the correct timing of EGFR and Hh activation to generate a normal pattern of cellular differentiation, 4) synergistic cellular alterations upon simultaneous activation of the Hh and EGFR pathways.\nAs a mild criticism, I don’t really understand the bases of the manuscript title “A single-cell analysis of Hh and EGFR-RAS: Independent signaling pathways prevent tumorigenesis”, as it is the fact that signaling pathways during normal development are deployed in an orderly fashion what prevent tumorigenesis. Perhaps the authors would like to give a second though to make the title more adjusted to the conclusions of the manuscript. Thus, it seems to me that something like\n“A single-cell analysis of Hh and EGFR-RAS: the timely deployment of these signaling pathways prevent tumorigenesis”\ncould be more adjusted to what they are describing.", "reviewer_3": "In this ms, Katja Rust and colleagues uses the follicle epithelium of Drosophila and combines single cell genomics, bionformatic analysis and functional genetics to identify the transcriptional landscapes driving tumorigenesis. In the first part of the ms, authors identify Zfh1 transcription factor as the key Hh signaling target driving EMT like state. In the second part, they show that Pointed transcription factor mediates the effects of EGFR/Ras on proliferation. In the last part of the ms, authors analyze the effects of co-activation of Hh and EGF/RAs and come to the conclusion that Pointes drives genomic instability. Unfortunately, on one hand, the quality of images to show the effects of all genetic manipulations on cell behavior (proliferation, EMT, etc) is not good. On the other hand, the writing is confusing, hard to follow, and, to a certain extent, devoted to specialists in the field of follicle development rather than to readers more interested in the fundamental consequence of oncogene activation on epithelial tissues. The main message of the paper is indeed unclear. Most experiments are based on overexpression experiments and many claims (eg. Pointed mediates chromosomal instability downstream of EGF-Ras) are not substantiated by bona fide epistatic analysis. Many other conclusions are just based on correlations. Overall, the ms is in a highly preliminary state.", "reviewer_4": "Rust et al. investigate the consequences of pro-proliferative pathway overexpression on tissue homeostasis using the Drosophila follicular epithelium as model system. This epithelial tissue contains stem cells and is continuously developing throughout female adult life to produce egg chambers. Proliferation and differentiation of follicle cells are tightly regulated by multiple signaling pathways, including EGFR-Ras and Hedgehog (Hh). This work brings novelty in using single cell RNA-sequencing approaches to compare the transcriptional landscapes resulting from the targeting of several pro-proliferative pathways in the follicle cell lineage. The authors propose that either Hh or EGFR-Ras overactivation leads to a precursor stage of tumor development while the co-activation of those two pathways creates a synergistic effect and favors the progression towards an advanced cancer stage. The study is strengthened by convincing in vivo assays to assess the morphological and physiological consequences of such perturbations. This solid work brings new insights into signaling pathway interactions within a specific tissue and should have a strong impact in the field of tissue homeostasis and cancer development. Nevertheless, the following points should be addressed by the authors to improve clarity of the manuscript and solidity of the results:\nMajor points\n1) The result section of the manuscript is quite complex and difficult to read. As it stands, it is restricted to single cell transcriptomic algorithm users. To be addressed to a more general audience and gain in attractivity, the author should provide a more didactic version of the manuscript. Some aspects of the methodology and data representation are not explained at all, nor in the main text nor in the legends. This is the case in particular for the use of milo analysis to provide differential abundance plots and neighborhood graphs.\n2) While the data seems solid and the analysis well done, the authors have not made the code available. This is an integral part of the paper and access to the code should be provided.\n3) The role of Rasv12 and  top4.4 in polar cell differentiation is not clear. The authors show that polar cell fate is affected upon Rasv12 expression in polar cells, as seen by the downregulation of dpn, upd1 and upd3 expression (Supplementary Figure 4L). This is also supported by the decrease of Dpn detection in Rasv12 follicles (Supplementary 5B). These results suggest that Ras signaling inhibits polar cell differentiation rather than promoting it as the authors conclude. The role of  top4.4 in polar cell differentiation is not very clear since dpn expression seems lower than in control but higher than upon Rasv12 expression. Also, are Dpn protein levels higher in  top4.4 follicles than in controls (there is no control in Supplementary Figure 5A,B). Finally, there are more polar cells per cluster upon Rasv12 expression but there is no biological conclusion drawn from this result. Since polar cells are found in excess in early follicle stages and are eliminated by apoptosis before stage 5, the extra polar cells per cluster phenotype could result from an immature differentiation state or from an apoptosis downregulation. It would be interesting to look at apoptotic markers in this condition and more generally to document the status of apoptosis in Rasv12 follicles?\n4) The authors show that sustained EGFR-Ras overactivation blocks the entry of MB follicle cells to endocycles and they suggest that this effect is mediated by pnt. However, the demonstration is rather correlative with a phenocopy of pnt and Rasv12 overexpression phenotypes. A decrease in pnt expression in Rasv12 follicles should be made to reach that conclusion. In addition, it is already known that pnt is a target of EGFR signaling, hence the sentence “(…) ovarioles with pnt overexpression contained mitotic cells across all stages, suggesting that pnt is a key target of the EGFR-Ras pathway (Fig. 4J-K)” cannot be written.\nMinor points\n1) Regarding the fluidity of the manuscript, it is difficult to follow since the authors examine many different aspects that are not always linked and some conclusions do not fit easily with the general message. For instance, the second paragraph of the first part of the result section is fairly substantial in focusing on new insights provided by the single cell RNA-seq performed in the wild type condition, which does not fit with the title of this section. While the content of this paragraph is interesting, it is not connected to the rest of the section and distracts the reader from the main focus.\n2) The authors examine the mitosis to endocycle transition, which occurs at stage 6, in different genetic contexts. They observe PH3 staining in the latest follicles upon Rasv12 expression, as opposed to controls, but it could be because follicles are maintained in an early stage and thus do not reach the switch to endocycling. How were follicle stages assessed in Rasv12 follicles, given that regular criteria for staging, such as follicle size and shape are lost? Along this line, FC 6+ cells are largely under-represented in the Rasv12 single cell transcriptome.\n3) The authors show that pnt overexpression in FCs blocks the switch to endocycles. However, posterior follicle cells are known to express pnt following EGFR activation beyond stage 6, but they nevertheless switch to endocycling. It would be interesting to comment on that difference.\n4) The authors mention in the text some Zfh1+ and Eya+ cells in reference to Figure 5D-E, but Eya staining is not shown in the figure.\n5) There is a reference to Figure S6K in the text but Figure S6 stops with the H panel. In addition, the figure legend goes up to panel L.", "reviewer_5": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts."}, "author_response": "RESPONSE TO REVIEWER COMMENTS\nReviewer #1 (Remarks to the Author):\nReviewer Comments on “A single-cell analysis of Hh and EGFR-Ras: Independent signaling pathways prevent\ntumorigenesis”\nRust et al. present a technically sophisticated study combining genetic perturbation and single-cell\ntranscriptomics to explore how Hh and EGFR-Ras signaling affect cell fate and proliferation in the Drosophila\nfollicle epithelium. The authors identify transcriptional hybrid states, altered cell cycle control, and overgrowth\nphenotypes under pathway co-activation, which they interpret as hallmarks of tumorigenesis. While the dataset\nis rich and the experimental system well-chosen, the study’s interpretive clarity and mechanistic depth are\nhampered by key conceptual, analytical, and structural weaknesses.\nMajor Points\n1. The manuscript suffers from a lack of a clear conceptual thread. The experimental flow often feels\nobservational rather than hypothesis-driven, with new datasets introduced without clear rationale. This impairs\nreadability and interpretability, even for domain experts. To improve clarity and engagement, the authors\nshould reorganize the results around discrete, testable questions and explicitly state the purpose of each\nexperimental step.\nWe thank the reviewer for the suggestion. We have restructured the results section to create a more streamlined\nmanuscript and focused on our key data. Specifically, we now concentrated on the Hh, EGFR, Ras and co-\noveractivation datasets and reorganized the results, starting each section with a clear question or aim.\n2. The assertion that Hh and EGFR-Ras function independently is not supported by mechanistic data. The\npathways converge on shared transcriptional targets and exhibit synergistic phenotypes. Without epistasis\nexperiments or systematic pathway activity measurements (e.g., ptc-GFP, dpERK) in single vs. double mutant\nbackgrounds, “independent” is an overstatement. The term “functionally parallel” would be more appropriate\nunless cross-regulation is explicitly ruled out.\nWe agree with the reviewer’s comment and therefore addressed pathway independence experimentally (Fig. 1 and\nS1). Our quantifications of pathway reporter activity and epistasis experiments suggest that the pathways are indeed\nindependent. We added the following section in the results: “EGFR-Ras signaling and the Hh pathway act\nindependently in the follicle epithelium”.\nWe also investigated whether reduction of either pathway in the double overactivation background restores the\nrespective phenotypes, although we did not include this data in the manuscript. This experiment, too, suggests that\nboth pathways are independent (see attached figure, n = 82 (Raf-RNAi), 70 (smo-RNAi)).\nWe further measured pathway activity in the co-overactivation background and found similar levels (6 days post\ntemperature shift: dpERK: EGFRCA vs HhOE,EGFRCA: p = 0.1441 (ns), RasV12 vs HhOE, RasV12: p = 0.4652 (ns),\nptc-cherry: HhOE vs HhOE,EGFRCA: p = 0.1985 (ns), vs HhOE,RasV12: p = 0.03212 (*), p-values from Kruskal-Wallis tests).\nTogether, these results support that no direct cross-regulation between the Hh and EGFR-Ras pathways takes place.\nOvarioles expressing HhOE,RasV12 under the 109-30 promoter combined with Raf-RNAi (left) or smo-RNAi (right) and\nstained for DAPI (blue), Eya (green) and ECad (magenta). Depletion of Raf restores a HhOE-like phenotype with large\nstalk-like areas and lacking MB cells from mature cysts. Depletion of smo restores a RasV12-like phenotype with cyst\nfusions. Note that we temperature-shifted for 6 days.\n3. Despite generating a large and high-quality scRNA-seq dataset, the analysis remains descriptive. No\ntrajectory inference or fate-mapping is performed, even though the central claims revolve around hybrid states\nand differentiation arrest. Methods such as Monocle 3, Palantir, or scVelo could clarify whether mutant cells\ndeviate from canonical lineage trajectories or are blocked at specific transitions.\nWe performed Monocle3 analysis and found that the results indeed support our claims (see Fig. 2,6, S4 and S0). We\nthank the reviewer for this fruitful suggestion.\n4. While the co-activation phenotypes resemble dysplasia, the study lacks definitive lineage tracing or clonal\nanalysis to establish tumor origin and progression. The use of broad drivers (e.g., 109-30-Gal4) precludes\nspatial or temporal precision. Tools such as MARCM, G-TRACE, or temporally restricted Gal80ts could\nstrengthen the argument for cell-autonomous tumor initiation.\nWe performed two sets of experiments to address these concerns:\n- We performed staged analysis of tumor growth (Fig. S12)\n- We applied several cell-type specific Gal4 drivers, including an additional driver, zfh1-Gal4, which allowed us\nto conclude that the tumor origin is the MB follicle cell population (Fig. S11)\nFrom our results we conclude that the tumor-initiation dependents on Gal4 activity in MB cells: “To test whether pFCs\nindeed give rise to this expansion of cells, we made use of Gal4 driver lines 12,60 targeting distinct follicle cell populations\nto express HhOE with either EGFRCA or RasV12 (Fig. S11A-F). We found that only Gal4 drivers with expression in MB\ncells caused tumor-like growth (Fig. S11G-N). This demonstrates that the aberrant expansion of Hh-EGFR/Ras cells is\nlikely caused by MB follicle cells retaining pFC character.”\nFurthermore, quantitative assessment of rescue phenotypes (e.g., zfh1-RNAi, pnt-RNAi) remains incomplete.\nWe added quantifications for all phenotypes described in the paper. The quantifications of zfh1- and pnt-RNAis,\nspecifically, can be found in Fig. 5Y and S6U.\n5. The conclusion that Hh induces EMT is based solely on transcriptional upregulation of EMT-associated\ngenes. No morphological or functional evidence of EMT, such as polarity loss, cell delamination, or motility, is\nprovided. Immunostaining for polarity markers (e.g., Crb, aPKC), adhesion molecules, and cytoskeletal\norganization should be used to validate this claim. Without such data, “EMT-like transcriptional state” is the\nappropriate framing.\nWe investigated the EMT phenotype in more depth, as suggested and summarized our results in the paragraph “Ectopic\nHh signaling induces EMT” in the Results section and in Figure 4. We now show that Hh overactivation induces Pbl\nand Htl using reporter lines. We also investigated cell polarity and confirmed that Hh overactivation induces polarity\ndefects. Further, we applied live imaging analysis and found migration effects and evidence that Hh overactivated cells\ndisplay invasive migration. Please refer to Fig. 4 and Movies S1-3.\n6. Mutant cell clusters map poorly to wild-type references, raising concerns about misclassification. Marker\nmisexpression could mimic FSC/pFC expansion. The origin of the tumor-like overgrowth remains unclear.\nAdditional immunostaining, co-expression validation, and lineage tracing are necessary to support the\nconclusion that tumors arise from pFCs.\nWe added an additional cell-type specific Gal4 driver line, zfh1-Gal4, which allows us to discriminate between the pFCs\nand MB cells as tumor origin. Indeed, we find that MB cells and not pFCs are the cell type that induces tumorigenic\ngrowth (Fig. S11).\nPlease note that we considered performing lineage tracing analysis, but the only cell type that can be reliably traced in\nthe ovary is the FSC, as all other cells are continuously replaced. As our data show that Gal4 activity in FSCs does not\ninduce tumor growth, we therefore refrained from performing lineage tracing.\nIn addition, we performed pseudotime analysis, which supports our initial claim that follicle cells with Hh-EGFR/Ras co-\noveractivation do not differentiate beyond the initial stages of follicle cell development (Fig. 6O and S4D-G). We also\nperformed an additional immunostaining analysis of BrC, which is expressed from Stage 6 of WT MB differentiation\n(Fig. S8F). We find that follicle cells with Hh-EGFR/Ras co-overactivation do not induce the expression of BrC, except\nin very few cases in which BrC positive cells were associated with germline cysts with WT-like morphology. We added\nthis information in the manuscript: “These cells did not induce the expression of BrC, a marker of Stage 6 MB cells,\nexcept in very rare cases (data not shown).” Please refer to the figure below.\nOvarioles expressing HhOE and either EGFRCA (upper panel) or RasV12 (lower panel) stained for DAPI (blue), BrC\n(green) and pH3 (magenta). We occasionally detected BrC positive cells (green line), which were associated with\ngermline cysts.\n7. The authors repeatedly refer to a “hybrid state” to describe cells that co-express markers of both\nundifferentiated and differentiated follicle cell fates. However, the term “hybrid state” has specific\nconnotations in developmental and cancer biology, typically implying a stable or metastable identity with\nfunctional consequences, such as altered plasticity, lineage potential, or behavior. In this study, the\ndesignation appears to be based solely on transcriptional co-expression, without supporting evidence for\nfunctional hybridity or trajectory disruption. The authors should therefore define more precisely what\nthey mean by “hybrid,” clarify whether this is a transient, transcriptional, or functionally stable state, and consider\nusing a more neutral term (e.g., “mixed transcriptional profile”) unless further dynamic or functional validation\nis provided.\nAs suggested, we now refer to this state as a “mixed transcriptional state”. We do raise the reader’s attention to a\nsimilar “hybrid state” in cancer metastasis in the discussion.\n8. The manuscript surveys several signaling pathways (Wnt, JNK, Hippo), but the main mechanistic insights\nand tumorigenic phenotypes stem from Hh and EGFR-Ras overactivation. Including additional pathways\nwithout comparable depth or functional relevance diffuses the narrative and dilutes the manuscript's impact.\nThe authors should consider narrowing their focus to the Hh and EGFR-Ras axis—which clearly drives the key\nphenotypes—or explicitly justify the inclusion of other pathways with targeted analyses or integrative\ncomparisons. This would greatly enhance conceptual coherence and mechanistic clarity.\nAs suggested, we removed the Wnt, yki and Hep datasets and now focus on the Hh, EGFR, Ras and co-overactivation\ndatasets.\nAdditional comments:\nThe manuscript includes limited pH3 staining to show persistence of mitotic cells beyond stage 6 in EGFR or\nRas overactivation conditions, supporting disruption of the mitosis-to-endocycle transition. However, this\nanalysis is qualitative, not systematically quantified across genotypes, and is not extended to the double\nmutant tumor contexts where cell cycle misregulation is central to the conclusions.\nWe quantified phospho-Histone H3 staining across genotypes (Fig. 5O) and investigated phospho-Histone H3 in the\nco-overactivation background (Fig. 7L-M). Each ovariole in the co-overactivation background we examined showed the\nphenotype shown in Fig. 7L-M (n = 34 ovarioles for each condition).\nMoreover, other key claims, such as accelerated cycling, checkpoint evasion, and altered G1/G2 phase\ndynamics, are based entirely on transcriptomic inference. These would be significantly strengthened by\nincorporating functional assays such as EdU/BrdU incorporation for S-phase entry, FACS-based DNA content\nprofiling, and broader use of mitotic and G2/M markers. This would provide crucial validation for the\ncomputational predictions and enhance the mechanistic rigor of the study.\nWe concentrated on a more detailed analysis of the cell cycle. For this, we used phospho-Histone H3 staining and\nquantification and utilized the CycB-nls-RFP construct of the Fly-FUCCI system, which allowed us to identify cells in M\nand G1, respectively (Fig. 5I-O, 7L-S, S7B-G). We were able to confirm our cell cycle scoring results in the wildtype\nbackground (Fig. SB). Further, we show and quantify cell cycle defects in single and double overactivation backgrounds\n(Fig. 5I-O, 7L-S & S7C-G).\n- While Gal80ts permits temporal control, the kinetics of tumor initiation and transcriptional changes remain\nunresolved. A time-course analysis (e.g., staged scRNA-seq or live imaging of pathway reporters) could clarify\nthe sequence and causality of key phenotypic transitions.\nWe performed staged analysis of double overactivation phenotypes and combined them with pathway reporter analysis\n(Fig. S12). Our results show that pathway activity is induced shortly after temperature shift, in agreement with the timing\nof Gal4 system induction and then stays consistently active while the phenotypic alteration continuously increases with\ntime.\n- Reference mapping to wild-type atlases is used to support hybrid or misclassified cell identities, but mapping\nconfidence metrics (e.g., Seurat prediction scores or LISI values) are not reported. Including these would\nimprove interpretability and lend quantitative support to claims of lineage disruption.\nWe included mapping scores for each dataset in Fig. 2G (as a Dotplot representation), S4H-K (on UMAP plots) and\nS10F-G (Dotplot and UMAP plots).\nMinor Points\n• Figures are fragmented and key data (e.g., double mutant phenotypes) are scattered; consolidation would aid\ncomprehension.\nWe reorganized the results section and organized data in a more streamlined manner.\n• Statistical reporting is inconsistent. All n-values and p-values should be included; bar graphs should be\nreplaced with dot/violin plots.\nAll barplots have been replaced by violin plots. We also report all n and p-values as well as the statistical test applied\nfor each calculation in the figure legends.\n• Methodological transparency should be improved. Full computational parameters and code (e.g., for SCENIC,\nMilo, batch correction) should be shared via GitHub or Zenodo.\nWe now provide all scripts under the following Github page:\nhttps://github.com/KatjaRM/Anschuetz-SCS-Hh-and-EGFR-Ras\n• Terminology such as “tumor and “independent” should be used with greater precision and caution.\nWe agree with the reviewer. We now provide extensive experimental evidence that both pathways act independently\n(Fig. 1, S1D-M) and are therefore confident in the use of this term. We further assess several cancer hallmarks in the\ndouble overactivation backgrounds that support our conclusion that this co-overactivation results in tumors (Fig. 7K,\nS12, S13). In addition, we revised the text and use both terms only when mandated.\n• The discussion of parallels with human cancer should be grounded in conserved pathway logic (e.g.,\nZfh1/ZEB1, Pnt/ETS) rather than speculation.\nWe revised the discussion accordingly and added the following paragraph in the discussion: “In human cancer, the\nZfh1 homologs ZEB1/2 are relevant target genes downstream of Hh signaling, where they promote EMT and therefore\nmetastasis 77. Similarly, the Pnt homologs ETS1/2 are established targets of the MAPK signaling pathway in cancer\nand promote tumor proliferation and invasiveness 78. This highlights the high conservation of the Hh and EGFR-Ras\nsignaling pathways.”\nConclusion\nThis study addresses important questions in epithelial plasticity and oncogenic signaling using a powerful\nmodel and modern transcriptomic tools. However, its impact is undermined by conceptual overreach, narrative\ndisorganization, and a lack of mechanistic validation. Major revisions, including trajectory inference, targeted\nrescue and epistasis experiments, lineage tracing, and clarification of experimental logic, are necessary to\nrealize the full potential of this work. With these improvements, the manuscript would make a valuable\ncontribution to the field.\nWe thank the reviewer for their valuable comments. We believe that addressing each concern has strongly improved\nthe manuscript and are grateful for the time and effort the reviewer spent on revising our manuscript. We are confident\nthat we have addressed all comments comprehensively and hope that this erases the concerns.\nReviewer #2 (Remarks to the Author):\nThe authors use the follicular epithelium of the Drosophila ovary to address the contribution of different\nsignaling pathways to cell proliferation and differentiation. They first combine overexpression of the Hh ligand\nand/or constitutively activated EGFR and Ras1 with single-cell transcriptomics to define the transcriptional\nprofiles of the affected follicular cells. They are able to define several cell clusters based in their transcriptomic\nprofiles, identifying differentially expressed genes downstream of the affected signaling pathways. They also\nanalyze combined over-activation of the same pathways, and identify a highly proliferative phenotype of\nundifferentiated cells accompanied by novel transcriptomic signatures. Finally, the authors also do a\ncomprehensible phenotypic description of the consequences of their genetic manipulations, as well as\nepistatic analysis to better define the key components of Hh, EGFR and other signalling pathways involved in\nthe assignation of cell states.\nThis seems to me as a very significant and timely analysis in which a lot of effort has been put into the\ncomparison between transcriptomic signatures, the action of candidate signaling pathways and the\nidentification of the main components of these pathways through functional genetic analysis. The\nmethodology is aligned with the standards of the field, the description of the results accurate and in my view\nthe results support the many conclusions stated in the manuscript. I am not expert in the bioinformatic\nprocessing of single cell sequencing experiments, and consequently I cannot express a knowledgeable\nopinion on methods, methodology and data analyses.\nIn summary, I consider the manuscript a valuable contribution in the fields of cell signaling, cell signaling\npathways interactions, regulation of cell differentiation and proliferation and cooperative effects promoting\ntumoral development that will be of interest to a variety of scientist working in these and related areas, and I\nam quite happy to recommend its publication. To me the strongest points are: 1) identification of the main\ncomponents mediating the action of the Hh (zfh1) and EGFR (pointed) signaling pathways, 2) identification of\ncooperativity in the regulation of gene expression in response to these pathways, 3) critical contribution of the\ncorrect timing of EGFR and Hh activation to generate a normal pattern of cellular differentiation, 4) synergistic\ncellular alterations upon simultaneous activation of the Hh and EGFR pathways.\nWe thank the reviewer for their time and effort and their input.\nAs a mild criticism, I don’t really understand the bases of the manuscript title “A single-cell analysis of Hh and\nEGFR-RAS: Independent signaling pathways prevent tumorigenesis”, as it is the fact that signaling pathways\nduring normal development are deployed in an orderly fashion what prevent tumorigenesis. Perhaps the\nauthors would like to give a second though to make the title more adjusted to the conclusions of the\nmanuscript. Thus, it seems to me that something like\n“A single-cell analysis of Hh and EGFR-RAS: the timely deployment of these signaling pathways prevent\ntumorigenesis” could be more adjusted to what they are describing.\nWe agree that the previous version of the manuscript did not address the independence of the signaling pathways and\ntherefore addressed this question experimentally. We analyzed pathway activity reporters and performed epistasis\nexperiments which suggest that, indeed, the Hh and EGFR-Ras pathway act independent in follicle cells (Fig. 1, S1D-\nM). We therefore chose the following, revised title for our manuscript: “Independent Hh and EGFR-Ras pathway activity\nsustains epithelial homeostasis and prevents tumorigenesis”\nReviewer #3 (Remarks to the Author):\nIn this ms, Katja Rust and colleagues uses the follicle epithelium of Drosophila and combines single cell\ngenomics, bionformatic analysis and functional genetics to identify the transcriptional landscapes driving\ntumorigenesis. In the first part of the ms, authors identify Zfh1 transcription factor as the key Hh signaling\ntarget driving EMT like state. In the second part, they show that Pointed transcription factor mediates the\neffects of EGFR/Ras on proliferation. In the last part of the ms, authors analyze the effects of co-activation of\nHh and EGF/RAs and come to the conclusion that Pointes drives genomic instability. Unfortunately, on one\nhand, the quality of images to show the effects of all genetic manipulations on cell behavior (proliferation,\nEMT, etc) is not good. On the other hand, the writing is confusing, hard to follow, and, to a certain extent,\ndevoted to specialists in the field of follicle development rather than to readers more interested in the\nfundamental consequence of oncogene activation on epithelial tissues. The main message of the paper is\nindeed unclear. Most experiments are based on overexpression experiments and many claims (eg. Pointed\nmediates chromosomal instability downstream of EGF-Ras) are not substantiated by bona fide epistatic\nanalysis. Many other conclusions are just based on correlations. Overall, the ms is in a highly preliminary\nstate.\nWe thank the reviewer for their honest analysis and agree that the structure of the results section of our manuscript\nrequired fundamental reorganization. We have therefore:\n- Concentrated on the key findings in the new manuscript and removed datasets that we did not analyse in\ndepth\n- Optimized writing in order to make the manuscript accessible to a broad audience\n- Performed diverse experiments that confirm that the Hh and EGFR-Ras pathways act independently in early\nfollicle epithelial homeostasis (Fig. 1, S1D-M)\n- Added in-depth analysis of EMT induction (Fig. 4 and Movies S1-3)\n- Performed extensive analysis of cell cycle defects (Fig. 5G-O, 7L-S, S7B-G, S13)\n- Updated images of phenotypes and added extensive quantifications\nReviewer #4 (Remarks to the Author):\nRust et al. investigate the consequences of pro-proliferative pathway overexpression on tissue homeostasis\nusing the Drosophila follicular epithelium as model system. This epithelial tissue contains stem cells and is\ncontinuously developing throughout female adult life to produce egg chambers. Proliferation and\ndifferentiation of follicle cells are tightly regulated by multiple signaling pathways, including EGFR-Ras and\nHedgehog (Hh). This work brings novelty in using single cell RNA-sequencing approaches to compare the\ntranscriptional landscapes resulting from the targeting of several pro-proliferative pathways in the follicle cell\nlineage. The authors propose that either Hh or EGFR-Ras overactivation leads to a precursor stage of tumor\ndevelopment while the co-activation of those two pathways creates a synergistic effect and favors the\nprogression towards an advanced cancer stage. The study is strengthened by convincing in vivo assays to\nassess the morphological and physiological consequences of such perturbations. This solid work brings new\ninsights into signaling pathway interactions within a specific tissue and should have a strong impact in the\nfield of tissue homeostasis and cancer development.\nWe thank the reviewer for their analysis, effort and time.\nNevertheless, the following points should be addressed by the authors to improve clarity of the manuscript\nand solidity of the results:\nMajor points\n1) The result section of the manuscript is quite complex and difficult to read. As it stands, it is restricted to\nsingle cell transcriptomic algorithm users. To be addressed to a more general audience and gain in attractivity,\nthe author should provide a more didactic version of the manuscript. Some aspects of the methodology and\ndata representation are not explained at all, nor in the main text nor in the legends. This is the case in particular\nfor the use of milo analysis to provide differential abundance plots and neighborhood graphs.\nWe revised the results section and reorganized it entirely. We now concentrate on our key results and present all data\nin a more accessible manner. We also provide a more detailed explanation of the milo approach: “To assess the effects\nthat either signaling pathway had on each cell type, we performed differential abundance testing, which tests whether\nspecific cell types or states are over- or underrepresented between conditions 37.” Further, we do not discuss\nNeighborhood graphs in depth in the revised manuscript, although we still provide this data in the supplementary\ninformation (Fig. S4A-C, S10I).\n2) While the data seems solid and the analysis well done, the authors have not made the code available. This\nis an integral part of the paper and access to the code should be provided.\nAll scripts are now publicly accessible under https://github.com/KatjaRM/Anschuetz-SCS-Hh-and-EGFR-Ras.\n3) The role of Rasv12 and top4.4 in polar cell differentiation is not clear. The authors show that polar cell fate\nis affected upon Rasv12 expression in polar cells, as seen by the downregulation of dpn, upd1 and upd3\nexpression (Supplementary Figure 4L). This is also supported by the decrease of Dpn detection in Rasv12\nfollicles (Supplementary 5B). These results suggest that Ras signaling inhibits polar cell differentiation rather\nthan promoting it as the authors conclude. The role of top4.4 in polar cell differentiation is not very clear since\ndpn expression seems lower than in control but higher than upon Rasv12 expression. Also, are Dpn protein\nlevels higher in top4.4 follicles than in controls (there is no control in Supplementary Figure 5A,B). Finally,\nthere are more polar cells per cluster upon Rasv12 expression but there is no biological conclusion drawn\nfrom this result. Since polar cells are found in excess in early follicle stages and are eliminated by apoptosis\nbefore stage 5, the extra polar cells per cluster phenotype could result from an immature differentiation state\nor from an apoptosis downregulation. It would be interesting to look at apoptotic markers in this condition and\nmore generally to document the status of apoptosis in Rasv12 follicles?\nIn response to this comment, we analyzed the polar cell specific effects of RasV12 further and found that, in contrast to\nLtop4.4, RasV12 induces ectopic mitosis in polar cells (Fig. S5I-M). We also depleted MAPK activity in polar cells using\ntwo transgenic lines (ERKDN and Raf-RNAi), which did not affect polar cell numbers (Fig. S5H). Additionally, our analysis\nof pathway activity indicates that RasV12 has a substantially higher effect on MAPK activity. Together, we conclude that\nRasV12 induces high levels of MAPK activity which results in ectopic mitosis in polar cells, causing the increased polar\ncell number: “To test whether RasV12 indeed exerts effects on polar cells distinct from those induced by EGFRCA we\nexamined polar cells further. Polar cell specific induction of EGFRCA using upd-Gal4 did not result in any morphological\ndefects when compared to a wildtype control (Fig. S5E-F). In contrast, polar cell specific RasV12 expression significantly\nincreased the number of polar cells per cluster and caused a double row stalk phenotype (Fig. S5G-H). Polar cell\nspecific expression of ERKDN or Raf-RNAi did not alter polar cell numbers, suggesting that the MAPK-pathway is not\nrequired to be active in polar cells for their differentiation (Fig. S5H). However, we noted that RasV12 polar cells were\noccasionally mitotic (as indicated by staining for the mitotic marker, phospho-Histone H3), while we did not observe\nmitotic control and EGFRCA polar cells, in agreement with previous reports 41 (Fig. S5I-M). As induction of proliferation\nis a well-described effect of the EGFR-Ras pathway and in agreement with our analysis on the pathway reporter dpERK,\nwe conclude that the RasV12 transgene induces MAPK signaling more effectively than EGFRCA, resulting in ectopic\nmitotic divisions of polar cells.”\nOur results are in line with an interpretation where RasV12 is able to induce higher levels of MAPK activity than EGFRCA,\nwhich causes an aberrant expansion of the polar cell pool. Prolonged mitosis blocks differentiation in many\ndevelopmental contexts. Therefore, it is tempting to speculate that ectopic mitosis in early stages of polar cell-fated\npFCs induced by RasV12 may block polar cell differentiation. We attempted to stain for Dcp1 in ovarioles with expression\nof RasV12 specifically in polar cells with upd-Gal4 but very few flies of the appropriate genotype reach adulthood, so we\ncould not obtain a sufficient sample size for a conclusive analysis. We instead decided to use the limited number of\nflies we obtained to complete the high priority goal of quantifying the mitosis defects. As the effect of RasV12 signaling\non polar cell differentiation is not the main focus of this manuscript, a comprehensive investigation of this question is\nbeyond the scope of this work and would be more appropriately addressed in a follow-up study..\n4) The authors show that sustained EGFR-Ras overactivation blocks the entry of MB follicle cells to endocycles\nand they suggest that this effect is mediated by pnt. However, the demonstration is rather correlative with a\nphenocopy of pnt and Rasv12 overexpression phenotypes. A decrease in pnt expression in Rasv12 follicles\nshould be made to reach that conclusion. In addition, it is already known that pnt is a target of EGFR signaling,\nhence the sentence “(…) ovarioles with pnt overexpression contained mitotic cells across all stages,\nsuggesting that pnt is a key target of the EGFR-Ras pathway (Fig. 4J-K)” cannot be written.\nWe agree with the reviewer and investigated mitosis in the background of EGFR and Ras overactivation combined with\npnt-RNAi. Indeed, this did not fully rescue ectopic mitosis (Fig. S7H-J). We therefore now conclude that pnt is not the\nonly crucial target gene of EGFR-Ras signaling: “Hence, pnt is one, but likely not the only, important target of EGFR-\nRas signaling in this process.”\nWe reference publications in the manuscript identifying Pnt as a Ras target gene and have removed the previous\nsentence. Eg. “E2f1 is a well-known cell cycle regulator required for G1 to S transition and Pnt induces cell cycle related\ngenes during neural development and is induced by Ras signaling 46–48.”\nMinor points\n1) Regarding the fluidity of the manuscript, it is difficult to follow since the authors examine many different\naspects that are not always linked and some conclusions do not fit easily with the general message. For\ninstance, the second paragraph of the first part of the result section is fairly substantial in focusing on new\ninsights provided by the single cell RNA-seq performed in the wild type condition, which does not fit with the\ntitle of this section. While the content of this paragraph is interesting, it is not connected to the rest of the\nsection and distracts the reader from the main focus.\nWe reorganized the results section, which is now more streamlined.\n2) The authors examine the mitosis to endocycle transition, which occurs at stage 6, in different genetic\ncontexts. They observe PH3 staining in the latest follicles upon Rasv12 expression, as opposed to controls,\nbut it could be because follicles are maintained in an early stage and thus do not reach the switch to\nendocycling. How were follicle stages assessed in Rasv12 follicles, given that regular criteria for staging, such\nas follicle size and shape are lost? Along this line, FC 6+ cells are largely under-represented in the Rasv12\nsingle cell transcriptome.\nCorrect, late stage follicle cells are underrepresented in the RasV12 as well as EGFRCA datasets (Fig. 2B-C). In RasV12\novarioles this is also reflected in the phenotype. We note in the manuscript: “In ovarioles with overexpression of RasV12,\nthe normal structure of the ovariole was completely disrupted and follicles rarely formed at all (Fig. 1F).”\nWe attempted to use differentiation markers (including BrC and eya) to stage follicle cells but found that these markers\ncannot provide sufficient resolution to time postmitotic follicle cells in the wildtype context (see Fig. S8A and F).\nTherefore, we instead staged follicles based on DAPI morphology of nurse cells as previously described (Jia et al.,\nTo address whether MB follicle cells associated with late stage germline cysts differentiate, we analyzed eya and BrC\nexpression. In WT ovarioles, Stages shortly after mitosis downregulate Eya and BrC is expressed shortly before MB\ncells exit mitosis (Fig. S8). We found that Hh overactivation expands eya expression and identified ectopic HhOE mitotic\ncells, which are Eya positive (Fig. S8). At the same time, BrC expression is only induced in a few HhOE MB cells,\nsuggesting that ectopic mitosis induced by HhOE is a consequence of delayed differentiation. In contrast, the expression\nstatus of eya and BrC in EGFR-Ras overactivated MB cells displaying ectopic mitosis suggests that these cells are\ncompetent to reach a differentiation status equivalent to endocycling MB cells (Fig. S8).\n3) The authors show that pnt overexpression in FCs blocks the switch to endocycles. However, posterior\nfollicle cells are known to express pnt following EGFR activation beyond stage 6, but they nevertheless switch\nto endocycling. It would be interesting to comment on that difference.\nWe thank the reviewer for raising this important point and now address it in the discussion: “Notably, Pnt is known to\nbe induced by EGFR signaling in posterior follicle cells past Stage 6, where it promotes the expression of midline to\nmediate the posterior follicle cell fate and hence actively promotes differentiation of MB cells that have already entered\nthe endocycle 78. This indicates that, while EGFR-Ras signaling must be inactive for cells to enter endocycling,\nactivation of EGFR-Ras signaling postmitotic MB is insufficient to induce reentry into mitosis. Future studies will have\nto address whether this depends on the exact timing or magnitude of EGFR-Ras activity and which target genes besides\npnt are relevant.”\n4) The authors mention in the text some Zfh1+ and Eya+ cells in reference to Figure 5D-E, but Eya staining is\nnot shown in the figure.\nWe corrected the manuscript accordingly: “We stained for markers of differentiation and found that most cells expressed\nZfh1, Eya and no or very few expressed the stalk cell marker LamC (Fig. 6F-K).” Fig. 6F-G show Zfh1 immunostaining,\nwhile Fig. 6H-I show Eya immunostaining.\n5) There is a reference to Figure S6K in the text but Figure S6 stops with the H panel. In addition, the figure\nlegend goes up to panel L.\nThe legend was corrected accordingly.\nReviewer #5 (Remarks to the Author):\nI co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the\nNature Communications initiative to facilitate training in peer review and to provide appropriate recognition\nfor Early Career Researchers who co-review manuscripts.\nWe thank the reviewer for their time and input!\nResponse to referees - NCOMMS-25-39031A\nWhile we did not receive additional input from Reviewer #3, we would like to thank them for their time and\nconsideration.\nReviewer #1 (Remarks to the Author):\nThis revised manuscript represents a substantial and thoughtful improvement over the previous\nversion. The authors have clearly invested significant effort in addressing both conceptual and\ntechnical concerns, particularly by restructuring the Results, narrowing the focus to Hh and EGFR–\nRas signaling, and adding extensive new experimental data.\nThe additional epistasis experiments and quantitative pathway reporter analyses considerably\nstrengthen the claim that Hh and EGFR–Ras do not cross-regulate each other at the level of pathway\nactivation. Similarly, the inclusion of pseudotime analyses, mapping confidence scores, staged\nphenotypic analyses, and quantitative rescue experiments markedly improves the rigor of the\nsingle-cell and genetic conclusions. The new data supporting an EMT-like phenotype downstream\nof Hh/Zfh1—combining transcriptional signatures with polarity defects and live imaging—are\nparticularly compelling and elevate the mechanistic depth of the study.\nWe thank the reviewer for their judgement and their effort to revising this manuscript.\nThat said, a few conceptual vulnerabilities remain. Most notably, the manuscript continues to use\nthe term “independent” in a way that may be interpreted more broadly than warranted by the data.\nWhile pathway activation appears independent, the strong transcriptional convergence and\ncooperative effects on proliferation and differentiation suggest functional convergence at\ndownstream regulatory nodes. A slightly more cautious framing—especially in the Abstract and\nDiscussion—would reduce the risk of overstatement.\nWe revised the title and text of the manuscript accordingly and now use the term “non-interacting” instead.\nWe would like to note, that we do not agree that our data provides direct evidence of transcriptional\nconvergence. We identify distinct downstream transcriptional targets, including zfh1 downstream of Hh\nsignaling and pnt downstream of EGFR-Ras signaling. Further, while both pathways promote proliferation,\nin ectopic Hh signaling this is accompanied by blocked differentiation while it is uncoupled from the\ndifferentiation status downstream of EGFR-Ras signaling. This suggests distinct regulatory modes\ndownstream of these pathways.\nLikewise, although the evidence for tumor-like growth upon co-activation of Hh and EGFR–Ras is\nstrong within the Drosophila ovary context, the use of the term “tumor” may still raise concerns for\nsome readers. An explicit definition of what constitutes a tumor in this system, and a brief\nacknowledgment of which classical cancer criteria are and are not met, would improve clarity and\npre-empt criticism.\nWe now use the word tumor more cautiously and instead refer to “tumor-like growth” or use “tumor model”.\nWe also added a “Limitations of the Study” section to discuss which cancer hallmarks our data support and\nwhich remain uncertain:\n“We find that follicle cells with co-overactivation of Hh and EGFR-Ras signaling fulfill multiple criteria of\ncancer. They are induced by overactivation of genes that are orthologous to well-known human oncogenes,\nloose normal tissue architecture, upregulate EMT, display metabolic deregulation, blocked differentiation\nand sustained proliferation. Further, they are ultimately lethal for the host organism. While co-overactivation\nwill certainly prove useful as a tumor model, future work will need to address, which additional hallmarks of\nhuman cancer, including for example replicative immortality, genome instability and induction of\ninflammation 84 , are met by this model.”\nThe identification of MB cells as the likely cell of origin for the overgrowth phenotype is a clear\nadvance, enabled by the use of additional cell-type–specific Gal4 drivers. However, because this\nconclusion relies on driver specificity rather than lineage tracing, the inherent limitations of this\napproach should be stated explicitly in the manuscript itself.\nWe have added a respective statement in our new “Limitations of the study” section:\n“Using cell-type specific Gal4-driver lines, we identified MB cells as the likely initiating cell population\npromoting tumor-like growth. This conclusion is limited by the specificity of the applied Gal4-driver tools.”\nFinally, while the single-cell analyses are comprehensive and technically sound, the Results section\nremains analytically dense. Select consolidation of scRNA-seq figures—without reducing data\navailability—could further sharpen the central biological narrative.\nWhile we understand that the sections of the manuscript addressing scRNA-seq data require some level of\nconcentration for readers less familiar with such analyses, we feel that reducing explanation further would\nlimit the informative value for readers interested in our application of scRNA-seq analysis tools. Each\nanalysis tool provides slightly different insights into the biology of these signaling pathways. Further, we\nuse reference mapping in an unconventional, yet highly constructive manner, showing that this algorithm is\nuseful for scientists analysing transcriptional effects of mutants.\nIn summary, this is now a strong and carefully executed study that makes a meaningful contribution\nto our understanding of how parallel signaling pathways jointly constrain epithelial homeostasis.\nWith modest adjustments to terminology, framing, and emphasis, the manuscript should be well\npositioned for acceptance.\nWe thank the reviewer for their support and are grateful for their contribution in improving this manuscript.\nReviewer #4 (Remarks to the Author):\nThe authors have drastically restructured the manuscript and restricted the scope of the study,\nwhich now focuses on Hh and EGFR signaling pathways, leading to an improved revised version\nthat gained in clarity and interest. The authors have also made substantial efforts to add convincing\nnew data and provide more detailed explanations of experimental procedures, therefore addressing\nall our concerns.\nWe thank the reviewer for their judgement.\nNevertheless, a couple of minor points should be addressed:\n- We agree with Reviewer 2 that the title of the manuscript does not reflect correctly the results of\nthe study. That Hh and EGFR pathways induce tumorigenesis when overactivated does not mean\nthat their physiological role is to prevent tumorigenesis. It is quite the opposite that would be\nrequired to be able to draw that conclusion, i.e if a loss of pathway activity would lead to\ntumorigenesis. As it stands the title (but also some statements in the abstract and other parts of\nthe manuscript) is misleading. The title is only true in the context of overactivation. In addition, it\nsuggests that there is a mechanism in place to limit pathway activity, hence preventing\ntumorigenesis, but this is not investigated in this work. Same for the following section title:\n\"Independent regulatory modes of proliferation prevents expansion of undifferentiated cells\", this\nis true upon pathway overactivation.\nWe recognize this mistake and have changed the title and reworded manuscript accordingly. We now\nexplain our view on the protective mechanism in more detail in the discussion:\n“Co-overactivation of either combination of these non-interacting pathways results in a significant expansion\nof the FSC pools. At the same time the loss of the activity of one of these pathways does not halt epithelial\ncell production 16,17. Therefore, compartmentalization of proliferative induction to several non-interacting\nsignaling pathways provides a protective mechanism during tissue homeostasis. It conserves proliferative\nactivity in the event of pathway loss while also safeguarding cells from the effects of ectopic pathway activity\nthat may be caused, for example, by mutations of proto-oncogenes or tumor suppressors.”\nAlong the same line, why the authors undertook a gain-of-function approach in the first place is not\nclear.\nA major goal of this study was to understand how signals regulating proliferation and differentiation in the\nearly FSC lineage interact. Previous work primarily used loss- or reduction-of-function approaches to\nestablish the necessity of these pathways for FSC self-renewal, proliferation, and differentiation. Our\nanalysis of pathway overactivation complements this by testing the sufficiency of EGFR–MAPK and Hh\nsignaling and examining whether their spatial restriction is required for proper lineage behavior.\nAlthough both pathways are required for normal proliferation, activation of either alone was insufficient to\ndrive lethal tumor-like overgrowth. In contrast, simultaneous activation of both pathways in main body cells\nproduced lethal tumor-like growth, revealing their cooperative potential. These findings help explain the\nspatial logic of pathway activity: both signals promote high proliferation in FSCs, whereas downstream\nreduction of EGFR–MAPK activity permits differentiation induced by Hh pathway activity.\nWe added in the manuscript:\n“While loss- and reduction-of-function analyses of EGFR-Ras and Hh signaling established their necessity\nfor follicle epithelial proliferation and differentiation, it is less well understood how spatial restriction of\npathway activity affects follicle epithelial homeostasis. Hence, in order to identify cell-type specific effects\nof pathway overactivation, we performed single-cell RNA-sequencing…”\n- Also in the section \"Independent regulatory modes of proliferation prevents expansion of\nundifferentiated cells\", the conclusion « co-overactivation of independent signaling pathways\nprotects the tissue from aberrant expansion of undifferentiated cells and therefore represents a\nsafety mechanism for epithelial homeostasis » is wrong.\nWe agree and have revised the respective section in the manuscript.\n- What are stalk cells in EGFRCA and RasV12 since follicles are fused?\nFor most of the manuscript we identified stalk cells bioinformatically or by marker expression. Therefore,\nwe assume that the reviewer is concerned about the identification of stalk areas for the measurement of\npathway activity in Figure 1K-L. For EGFRCA ovarioles stalk areas are usually recognizable as\nmorphologically distinct areas of follicle cells that accumulate between germline cysts in early stages\n(Figure 1I). Identification of stalk areas in RasV12 ovarioles are somewhat more difficult, yet we can detect\ncells expressing stalk cell markers at areas where cells are not directly associated with germline cells and\nhence selected such areas. We describe in the legend of Figure 1:\n“K-L) Quantification of Ptc-cherry (K) and dpERK (L) activity. We normalized measurements from the\nsecond stalk or areas with stalk-like morphology to R1 areas for each quantified picture.”\n- Panels C and Y from Figure 5 are very difficult to read with the color code used. Comparison of\naverage expression in the different conditions with wild-type is not possible.\nWe now present the quoted plots with the same color scheme for all genotypes.\nWe again want to thank their reviewer for very productive and very thoughtful suggestions that have helped\nus to improve the manuscript.\nReviewer #5 (Remarks to the Author):\nI co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part\nof the Nature Communications initiative to facilitate training in peer review and to provide\nappropriate recognition for Early Career Researchers who co-review manuscripts.\nWe thank the reviewer for their time and contribution."}]

Decision letter